{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/3d-object-detection/papers/ran/1","list_of":"/task/3d-object-detection","task":"3D Object Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":3,"rows_per_page":100,"rows":[1,100],"of":277,"counts":{"archive_papers_tagged":1576,"with_a_code_link":764,"where_syntology_ran_a_sample":277,"not_listed_spam_title":0,"listed":1576,"listed_where_code_ran":277,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":251,"every_run_a_failure_of_syntologys_instrument":26,"listed_with_a_run_with_no_instrument_failure":251,"listed_every_run_a_failure_of_syntologys_instrument":26,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/3d-object-detection/papers/ran/1","prev":null,"next":"/task/3d-object-detection/papers/ran/2","papers":[{"url":"/paper/mambafusion-height-fidelity-dense-global","slug":"mambafusion-height-fidelity-dense-global","title":"MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection","date":"2025-07-06","arxiv_id":"2507.04369","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/mambafusion-height-fidelity-dense-global#ran","syntology_url":"https://syntology.ai/paper/2507.04369","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2507.04369"}},"official":{"repos":["AutoLab-SAI-SJTU/MambaFusion"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/simulate-any-radar-attribute-controllable","slug":"simulate-any-radar-attribute-controllable","title":"Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding","date":"2025-06-03","arxiv_id":"2506.03134","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/simulate-any-radar-attribute-controllable#ran","syntology_url":"https://syntology.ai/paper/2506.03134","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.03134"}},"official":{"repos":["zhuxing0/sa-radar"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/psa-ssl-pose-and-size-aware-self-supervised","slug":"psa-ssl-pose-and-size-aware-self-supervised","title":"PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point Clouds","date":"2025-03-18","arxiv_id":"2503.13914","repositories_listed":0,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":2,"n_no_contract":5,"n_pointer_only":4,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 2 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/psa-ssl-pose-and-size-aware-self-supervised#ran","syntology_url":"https://syntology.ai/paper/2503.13914","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.13914"}},"official":null}},{"url":"/paper/state-space-model-meets-transformer-a-new-1","slug":"state-space-model-meets-transformer-a-new-1","title":"State Space Model Meets Transformer: A New Paradigm for 3D Object Detection","date":"2025-03-18","arxiv_id":"2503.14493","repositories_listed":1,"syntology":{"n":10,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/state-space-model-meets-transformer-a-new-1#ran","syntology_url":"https://syntology.ai/paper/2503.14493","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.14493"}},"official":null}},{"url":"/paper/roco-sim-enhancing-roadside-collaborative","slug":"roco-sim-enhancing-roadside-collaborative","title":"RoCo-Sim: Enhancing Roadside Collaborative Perception through Foreground Simulation","date":"2025-03-13","arxiv_id":"2503.10410","repositories_listed":1,"syntology":{"n":5,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/roco-sim-enhancing-roadside-collaborative#ran","syntology_url":"https://syntology.ai/paper/2503.10410","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.10410"}},"official":{"repos":["duyuwen-duen/roco-sim"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/accelerate-3d-object-detection-models-via","slug":"accelerate-3d-object-detection-models-via","title":"Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning","date":"2025-03-11","arxiv_id":"2503.08101","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/accelerate-3d-object-detection-models-via#ran","syntology_url":"https://syntology.ai/paper/2503.08101","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.08101"}},"official":{"repos":["iseri27/tg_gbc"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-to-detect-objects-from-multi-agent","slug":"learning-to-detect-objects-from-multi-agent","title":"Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual Labels","date":"2025-03-11","arxiv_id":"2503.08421","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-to-detect-objects-from-multi-agent#ran","syntology_url":"https://syntology.ai/paper/2503.08421","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.08421"}},"official":{"repos":["xmuqimingxia/dota"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/ov-scan-semantically-consistent-alignment-for","slug":"ov-scan-semantically-consistent-alignment-for","title":"OV-SCAN: Semantically Consistent Alignment for Novel Object Discovery in Open-Vocabulary 3D Object Detection","date":"2025-03-09","arxiv_id":"2503.06435","repositories_listed":0,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/ov-scan-semantically-consistent-alignment-for#ran","syntology_url":"https://syntology.ai/paper/2503.06435","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.06435"}},"official":null}},{"url":"/paper/codiff-conditional-diffusion-model-for","slug":"codiff-conditional-diffusion-model-for","title":"CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection","date":"2025-02-17","arxiv_id":"2502.14891","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/codiff-conditional-diffusion-model-for#ran","syntology_url":"https://syntology.ai/paper/2502.14891","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.14891"}},"official":{"repos":["huangzhe885/codiff"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/towards-flexible-3d-perception-object-centric","slug":"towards-flexible-3d-perception-object-centric","title":"Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection","date":"2024-12-06","arxiv_id":"2412.05154","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/towards-flexible-3d-perception-object-centric#ran","syntology_url":"https://syntology.ai/paper/2412.05154","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.05154"}},"official":{"repos":["ghostish/objectcentricocccompletion"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/bootstraping-clustering-of-gaussians-for-view","slug":"bootstraping-clustering-of-gaussians-for-view","title":"Bootstraping Clustering of Gaussians for View-consistent 3D Scene Understanding","date":"2024-11-29","arxiv_id":"2411.19551","repositories_listed":1,"syntology":{"n":12,"n_ran":12,"n_constructed":0,"n_ran_checked":11,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":9,"n_pointer_only":12,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 2 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bootstraping-clustering-of-gaussians-for-view#ran","syntology_url":"https://syntology.ai/paper/2411.19551","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.19551"}},"official":{"repos":["wb014/FreeGS"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/gaussianpretrain-a-simple-unified-3d-gaussian","slug":"gaussianpretrain-a-simple-unified-3d-gaussian","title":"GaussianPretrain: A Simple Unified 3D Gaussian Representation for Visual Pre-training in Autonomous Driving","date":"2024-11-19","arxiv_id":"2411.12452","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/gaussianpretrain-a-simple-unified-3d-gaussian#ran","syntology_url":"https://syntology.ai/paper/2411.12452","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.12452"}},"official":{"repos":["public-bots/gaussianpretrain"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/v2x-r-cooperative-lidar-4d-radar-fusion-for","slug":"v2x-r-cooperative-lidar-4d-radar-fusion-for","title":"V2X-R: Cooperative LiDAR-4D Radar Fusion for 3D Object Detection with Denoising Diffusion","date":"2024-11-13","arxiv_id":"2411.08402","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/v2x-r-cooperative-lidar-4d-radar-fusion-for#ran","syntology_url":"https://syntology.ai/paper/2411.08402","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.08402"}},"official":{"repos":["ylwhxht/v2x-r"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/imov3d-learning-open-vocabulary-point-clouds","slug":"imov3d-learning-open-vocabulary-point-clouds","title":"ImOV3D: Learning Open-Vocabulary Point Clouds 3D Object Detection from Only 2D Images","date":"2024-10-31","arxiv_id":"2410.24001","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/imov3d-learning-open-vocabulary-point-clouds#ran","syntology_url":"https://syntology.ai/paper/2410.24001","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.24001"}},"official":{"repos":["yangtiming/imov3d"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mvsdet-multi-view-indoor-3d-object-detection","slug":"mvsdet-multi-view-indoor-3d-object-detection","title":"MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane Sweeps","date":"2024-10-28","arxiv_id":"2410.21566","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mvsdet-multi-view-indoor-3d-object-detection#ran","syntology_url":"https://syntology.ai/paper/2410.21566","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.21566"}},"official":{"repos":["pixie8888/mvsdet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/deepinteraction-multi-modality-interaction","slug":"deepinteraction-multi-modality-interaction","title":"DeepInteraction++: Multi-Modality Interaction for Autonomous Driving","date":"2024-08-09","arxiv_id":"2408.05075","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deepinteraction-multi-modality-interaction#ran","syntology_url":"https://syntology.ai/paper/2408.05075","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.05075"}},"official":{"repos":["fudan-zvg/deepinteraction"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/l4dr-lidar-4dradar-fusion-for-weather-robust","slug":"l4dr-lidar-4dradar-fusion-for-weather-robust","title":"L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection","date":"2024-08-07","arxiv_id":"2408.03677","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/l4dr-lidar-4dradar-fusion-for-weather-robust#ran","syntology_url":"https://syntology.ai/paper/2408.03677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.03677"}},"official":{"repos":["ylwhxht/l4dr"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/harnessing-uncertainty-aware-bounding-boxes","slug":"harnessing-uncertainty-aware-bounding-boxes","title":"Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection","date":"2024-08-01","arxiv_id":"2408.00619","repositories_listed":1,"syntology":{"n":15,"n_ran":15,"n_constructed":0,"n_ran_checked":15,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":0,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/harnessing-uncertainty-aware-bounding-boxes#ran","syntology_url":"https://syntology.ai/paper/2408.00619","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.00619"}},"official":{"repos":["Ruiyang-061X/UA3D"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/lion-linear-group-rnn-for-3d-object-detection","slug":"lion-linear-group-rnn-for-3d-object-detection","title":"LION: Linear Group RNN for 3D Object Detection in Point Clouds","date":"2024-07-25","arxiv_id":"2407.18232","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/lion-linear-group-rnn-for-3d-object-detection#ran","syntology_url":"https://syntology.ai/paper/2407.18232","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.18232"}},"official":{"repos":["happinesslz/LION"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/dvpe-divided-view-position-embedding-for","slug":"dvpe-divided-view-position-embedding-for","title":"DVPE: Divided View Position Embedding for Multi-View 3D Object Detection","date":"2024-07-24","arxiv_id":"2407.16955","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dvpe-divided-view-position-embedding-for#ran","syntology_url":"https://syntology.ai/paper/2407.16955","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.16955"}},"official":{"repos":["dop0/dvpe"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/monowad-weather-adaptive-diffusion-model-for","slug":"monowad-weather-adaptive-diffusion-model-for","title":"MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection","date":"2024-07-23","arxiv_id":"2407.16448","repositories_listed":1,"syntology":{"n":26,"n_ran":15,"n_constructed":0,"n_ran_checked":14,"n_instrument":1,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 1 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/monowad-weather-adaptive-diffusion-model-for#ran","syntology_url":"https://syntology.ai/paper/2407.16448","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.16448"}},"official":{"repos":["visualaikhu/monowad"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":11,"ran_from_kinds":["official"]}}},{"url":"/paper/open-object-wise-position-embedding-for-multi","slug":"open-object-wise-position-embedding-for-multi","title":"OPEN: Object-wise Position Embedding for Multi-view 3D Object Detection","date":"2024-07-15","arxiv_id":"2407.10753","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/open-object-wise-position-embedding-for-multi#ran","syntology_url":"https://syntology.ai/paper/2407.10753","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.10753"}},"official":{"repos":["AlmoonYsl/OPEN"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/repvf-a-unified-vector-fields-representation","slug":"repvf-a-unified-vector-fields-representation","title":"RepVF: A Unified Vector Fields Representation for Multi-task 3D Perception","date":"2024-07-15","arxiv_id":"2407.10876","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/repvf-a-unified-vector-fields-representation#ran","syntology_url":"https://syntology.ai/paper/2407.10876","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.10876"}},"official":{"repos":["jbji/repvf"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/semi-supervised-3d-object-detection-with-1","slug":"semi-supervised-3d-object-detection-with-1","title":"Semi-supervised 3D Object Detection with PatchTeacher and PillarMix","date":"2024-07-13","arxiv_id":"2407.09787","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/semi-supervised-3d-object-detection-with-1#ran","syntology_url":"https://syntology.ai/paper/2407.09787","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.09787"}},"official":{"repos":["littlepey/ptpm"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/mos-model-synergy-for-test-time-adaptation-on","slug":"mos-model-synergy-for-test-time-adaptation-on","title":"MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection","date":"2024-06-21","arxiv_id":"2406.14878","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mos-model-synergy-for-test-time-adaptation-on#ran","syntology_url":"https://syntology.ai/paper/2406.14878","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.14878"}},"official":{"repos":["zhuoxiao-chen/mos"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/dpo-dual-perturbation-optimization-for-test","slug":"dpo-dual-perturbation-optimization-for-test","title":"DPO: Dual-Perturbation Optimization for Test-time Adaptation in 3D Object Detection","date":"2024-06-19","arxiv_id":"2406.13891","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/dpo-dual-perturbation-optimization-for-test#ran","syntology_url":"https://syntology.ai/paper/2406.13891","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.13891"}},"official":{"repos":["jo-wang/dpo"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/voxel-mamba-group-free-state-space-models-for","slug":"voxel-mamba-group-free-state-space-models-for","title":"Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection","date":"2024-06-15","arxiv_id":"2406.10700","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/voxel-mamba-group-free-state-space-models-for#ran","syntology_url":"https://syntology.ai/paper/2406.10700","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.10700"}},"official":{"repos":["gwenzhang/voxel-mamba"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/shelf-supervised-multi-modal-pre-training-for","slug":"shelf-supervised-multi-modal-pre-training-for","title":"Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection","date":"2024-06-14","arxiv_id":"2406.10115","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/shelf-supervised-multi-modal-pre-training-for#ran","syntology_url":"https://syntology.ai/paper/2406.10115","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.10115"}},"official":{"repos":["meharkhurana03/cm3d"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/efm3d-a-benchmark-for-measuring-progress","slug":"efm3d-a-benchmark-for-measuring-progress","title":"EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models","date":"2024-06-14","arxiv_id":"2406.10224","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/efm3d-a-benchmark-for-measuring-progress#ran","syntology_url":"https://syntology.ai/paper/2406.10224","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.10224"}},"official":{"repos":["facebookresearch/efm3d"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/bevspread-spread-voxel-pooling-for-bird-s-eye-1","slug":"bevspread-spread-voxel-pooling-for-bird-s-eye-1","title":"BEVSpread: Spread Voxel Pooling for Bird's-Eye-View Representation in Vision-based Roadside 3D Object Detection","date":"2024-06-13","arxiv_id":"2406.08785","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":15,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/bevspread-spread-voxel-pooling-for-bird-s-eye-1#ran","syntology_url":"https://syntology.ai/paper/2406.08785","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.08785"}},"official":{"repos":["datongjie/bevspread"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/geminifusion-efficient-pixel-wise-multimodal","slug":"geminifusion-efficient-pixel-wise-multimodal","title":"GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer","date":"2024-06-03","arxiv_id":"2406.01210","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/geminifusion-efficient-pixel-wise-multimodal#ran","syntology_url":"https://syntology.ai/paper/2406.01210","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.01210"}},"official":{"repos":["jiadingcn/geminifusion"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/collaborative-novel-object-discovery-and-box","slug":"collaborative-novel-object-discovery-and-box","title":"Collaborative Novel Object Discovery and Box-Guided Cross-Modal Alignment for Open-Vocabulary 3D Object Detection","date":"2024-06-02","arxiv_id":"2406.00830","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/collaborative-novel-object-discovery-and-box#ran","syntology_url":"https://syntology.ai/paper/2406.00830","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.00830"}},"official":{"repos":["yangcaoai/CoDA_NeurIPS2023"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/hardness-aware-scene-synthesis-for-semi","slug":"hardness-aware-scene-synthesis-for-semi","title":"Hardness-Aware Scene Synthesis for Semi-Supervised 3D Object Detection","date":"2024-05-27","arxiv_id":"2405.17422","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/hardness-aware-scene-synthesis-for-semi#ran","syntology_url":"https://syntology.ai/paper/2405.17422","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.17422"}},"official":{"repos":["wzzheng/hass"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/diffubox-refining-3d-object-detection-with","slug":"diffubox-refining-3d-object-detection-with","title":"DiffuBox: Refining 3D Object Detection with Point Diffusion","date":"2024-05-25","arxiv_id":"2405.16034","repositories_listed":1,"syntology":{"n":16,"n_ran":14,"n_constructed":0,"n_ran_checked":11,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":16,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/diffubox-refining-3d-object-detection-with#ran","syntology_url":"https://syntology.ai/paper/2405.16034","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.16034"}},"official":{"repos":["cxy1997/DiffuBox"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/commonsense-prototype-for-outdoor","slug":"commonsense-prototype-for-outdoor","title":"Commonsense Prototype for Outdoor Unsupervised 3D Object Detection","date":"2024-04-25","arxiv_id":"2404.16493","repositories_listed":1,"syntology":{"n":20,"n_ran":19,"n_constructed":0,"n_ran_checked":19,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":19,"n_pointer_only":20,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 19 with no instrument failure: 0 honoured, 0 violated, 19 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/commonsense-prototype-for-outdoor#ran","syntology_url":"https://syntology.ai/paper/2404.16493","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.16493"}},"official":{"repos":["hailanyi/cpd"],"state":"official (archive's flag): 19 ran","n_ran":19,"n_constructed":0,"n_ran_no_instrument_failure":19,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/monocd-monocular-3d-object-detection-with","slug":"monocd-monocular-3d-object-detection-with","title":"MonoCD: Monocular 3D Object Detection with Complementary Depths","date":"2024-04-04","arxiv_id":"2404.03181","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":1,"n_ran_checked":4,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"6 ran (of which 1 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/monocd-monocular-3d-object-detection-with#ran","syntology_url":"https://syntology.ai/paper/2404.03181","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.03181"}},"official":{"repos":["elvintanhust/monocd"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":1,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-mae-masked-autoencoders-for-self","slug":"nerf-mae-masked-autoencoders-for-self","title":"NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields","date":"2024-04-01","arxiv_id":"2404.01300","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/nerf-mae-masked-autoencoders-for-self#ran","syntology_url":"https://syntology.ai/paper/2404.01300","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.01300"}},"official":{"repos":["zubair-irshad/NeRF-MAE"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/weak-to-strong-3d-object-detection-with-x-ray","slug":"weak-to-strong-3d-object-detection-with-x-ray","title":"Weak-to-Strong 3D Object Detection with X-Ray Distillation","date":"2024-03-31","arxiv_id":"2404.00679","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/weak-to-strong-3d-object-detection-with-x-ray#ran","syntology_url":"https://syntology.ai/paper/2404.00679","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.00679"}},"official":{"repos":["sakharok13/x-ray-teacher-patching-tools"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/ov-uni3detr-towards-unified-open-vocabulary","slug":"ov-uni3detr-towards-unified-open-vocabulary","title":"OV-Uni3DETR: Towards Unified Open-Vocabulary 3D Object Detection via Cycle-Modality Propagation","date":"2024-03-28","arxiv_id":"2403.19580","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ov-uni3detr-towards-unified-open-vocabulary#ran","syntology_url":"https://syntology.ai/paper/2403.19580","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.19580"}},"official":{"repos":["zhenyuw16/uni3detr"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/optimizing-lidar-placements-for-robust","slug":"optimizing-lidar-placements-for-robust","title":"Is Your LiDAR Placement Optimized for 3D Scene Understanding?","date":"2024-03-25","arxiv_id":"2403.17009","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/optimizing-lidar-placements-for-robust#ran","syntology_url":"https://syntology.ai/paper/2403.17009","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.17009"}},"official":{"repos":["ywyeli/place3d"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/is-fusion-instance-scene-collaborative-fusion","slug":"is-fusion-instance-scene-collaborative-fusion","title":"IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection","date":"2024-03-22","arxiv_id":"2403.15241","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/is-fusion-instance-scene-collaborative-fusion#ran","syntology_url":"https://syntology.ai/paper/2403.15241","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.15241"}},"official":{"repos":["yinjunbo/is-fusion"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/find-n-propagate-open-vocabulary-3d-object","slug":"find-n-propagate-open-vocabulary-3d-object","title":"Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments","date":"2024-03-20","arxiv_id":"2403.13556","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/find-n-propagate-open-vocabulary-3d-object#ran","syntology_url":"https://syntology.ai/paper/2403.13556","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.13556"}},"official":{"repos":["djamahl99/findnpropagate"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/rcooper-a-real-world-large-scale-dataset-for","slug":"rcooper-a-real-world-large-scale-dataset-for","title":"RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perception","date":"2024-03-15","arxiv_id":"2403.10145","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":10,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rcooper-a-real-world-large-scale-dataset-for#ran","syntology_url":"https://syntology.ai/paper/2403.10145","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.10145"}},"official":{"repos":["air-thu/dair-rcooper"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/simpb-a-single-model-for-2d-and-3d-object","slug":"simpb-a-single-model-for-2d-and-3d-object","title":"SimPB: A Single Model for 2D and 3D Object Detection from Multiple Cameras","date":"2024-03-15","arxiv_id":"2403.10353","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/simpb-a-single-model-for-2d-and-3d-object#ran","syntology_url":"https://syntology.ai/paper/2403.10353","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.10353"}},"official":{"repos":["nullmax-vision/simpb"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/liso-lidar-only-self-supervised-3d-object","slug":"liso-lidar-only-self-supervised-3d-object","title":"LISO: Lidar-only Self-Supervised 3D Object Detection","date":"2024-03-11","arxiv_id":"2403.07071","repositories_listed":1,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/liso-lidar-only-self-supervised-3d-object#ran","syntology_url":"https://syntology.ai/paper/2403.07071","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.07071"}},"official":{"repos":["baurst/liso"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/enhancing-3d-object-detection-with-2d","slug":"enhancing-3d-object-detection-with-2d","title":"Enhancing 3D Object Detection with 2D Detection-Guided Query Anchors","date":"2024-03-10","arxiv_id":"2403.06093","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/enhancing-3d-object-detection-with-2d#ran","syntology_url":"https://syntology.ai/paper/2403.06093","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.06093"}},"official":{"repos":["nullmax-vision/qaf2d"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/safdnet-a-simple-and-effective-network-for","slug":"safdnet-a-simple-and-effective-network-for","title":"SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object Detection","date":"2024-03-09","arxiv_id":"2403.05817","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/safdnet-a-simple-and-effective-network-for#ran","syntology_url":"https://syntology.ai/paper/2403.05817","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.05817"}},"official":{"repos":["zhanggang001/hednet"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/cn-rma-combined-network-with-ray-marching","slug":"cn-rma-combined-network-with-ray-marching","title":"CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoors Object Detection from Multi-view Images","date":"2024-03-07","arxiv_id":"2403.04198","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/cn-rma-combined-network-with-ray-marching#ran","syntology_url":"https://syntology.ai/paper/2403.04198","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.04198"}},"official":{"repos":["sercharles/cn-rma"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/tumtraf-v2x-cooperative-perception-dataset","slug":"tumtraf-v2x-cooperative-perception-dataset","title":"TUMTraf V2X Cooperative Perception Dataset","date":"2024-03-02","arxiv_id":"2403.01316","repositories_listed":3,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":1,"n_instrument":5,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 5 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/tumtraf-v2x-cooperative-perception-dataset#ran","syntology_url":"https://syntology.ai/paper/2403.01316","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.01316"}},"official":{"repos":["tum-traffic-dataset/coopdet3d","tum-traffic-dataset/tum-traffic-dataset-dev-kit","walzimmer/3d-bat"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/multicorrupt-a-multi-modal-robustness-dataset","slug":"multicorrupt-a-multi-modal-robustness-dataset","title":"MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection","date":"2024-02-18","arxiv_id":"2402.11677","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/multicorrupt-a-multi-modal-robustness-dataset#ran","syntology_url":"https://syntology.ai/paper/2402.11677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.11677"}},"official":{"repos":["ika-rwth-aachen/multicorrupt"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/beam-beta-distribution-ray-denoising-for","slug":"beam-beta-distribution-ray-denoising-for","title":"Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection","date":"2024-02-06","arxiv_id":"2402.03634","repositories_listed":2,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":10,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/beam-beta-distribution-ray-denoising-for#ran","syntology_url":"https://syntology.ai/paper/2402.03634","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.03634"}},"official":{"repos":["liewfeng/beam","liewfeng/raydn"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/mixsup-mixed-grained-supervision-for-label","slug":"mixsup-mixed-grained-supervision-for-label","title":"MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection","date":"2024-01-29","arxiv_id":"2401.16305","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/mixsup-mixed-grained-supervision-for-label#ran","syntology_url":"https://syntology.ai/paper/2401.16305","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.16305"}},"official":{"repos":["bravegroup/pointsam-for-mixsup"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/dcdet-dynamic-cross-based-3d-object-detector","slug":"dcdet-dynamic-cross-based-3d-object-detector","title":"DCDet: Dynamic Cross-based 3D Object Detector","date":"2024-01-14","arxiv_id":"2401.07240","repositories_listed":1,"syntology":{"n":11,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/dcdet-dynamic-cross-based-3d-object-detector#ran","syntology_url":"https://syntology.ai/paper/2401.07240","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.07240"}},"official":{"repos":["say2l/dcdet"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/dual-perspective-knowledge-enrichment-for","slug":"dual-perspective-knowledge-enrichment-for","title":"Dual-Perspective Knowledge Enrichment for Semi-Supervised 3D Object Detection","date":"2024-01-10","arxiv_id":"2401.05011","repositories_listed":1,"syntology":{"n":18,"n_ran":9,"n_constructed":0,"n_ran_checked":2,"n_instrument":7,"n_unverified":9,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":18,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 7 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/dual-perspective-knowledge-enrichment-for#ran","syntology_url":"https://syntology.ai/paper/2401.05011","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.05011"}},"official":{"repos":["tingxueronghua/dpke"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/robofusion-towards-robust-multi-modal-3d","slug":"robofusion-towards-robust-multi-modal-3d","title":"RoboFusion: Towards Robust Multi-Modal 3D Object Detection via SAM","date":"2024-01-08","arxiv_id":"2401.03907","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/robofusion-towards-robust-multi-modal-3d#ran","syntology_url":"https://syntology.ai/paper/2401.03907","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.03907"}},"official":{"repos":["adept-thu/RoboFusion"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/long-tailed-3d-detection-via-2d-late-fusion","slug":"long-tailed-3d-detection-via-2d-late-fusion","title":"Long-Tailed 3D Detection via Multi-Modal Fusion","date":"2023-12-18","arxiv_id":"2312.10986","repositories_listed":1,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":15,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/long-tailed-3d-detection-via-2d-late-fusion#ran","syntology_url":"https://syntology.ai/paper/2312.10986","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.10986"}},"official":{"repos":["mayechi/lt3d-lf"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/mono3dvg-3d-visual-grounding-in-monocular","slug":"mono3dvg-3d-visual-grounding-in-monocular","title":"Mono3DVG: 3D Visual Grounding in Monocular Images","date":"2023-12-13","arxiv_id":"2312.08022","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/mono3dvg-3d-visual-grounding-in-monocular#ran","syntology_url":"https://syntology.ai/paper/2312.08022","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.08022"}},"official":{"repos":["zhanyang-nwpu/mono3dvg"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/3d-copy-paste-physically-plausible-object-1","slug":"3d-copy-paste-physically-plausible-object-1","title":"3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection","date":"2023-12-08","arxiv_id":"2312.05277","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/3d-copy-paste-physically-plausible-object-1#ran","syntology_url":"https://syntology.ai/paper/2312.05277","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.05277"}},"official":{"repos":["gyhandy/3d-copy-paste"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/diffusion-ss3d-diffusion-model-for-semi-1","slug":"diffusion-ss3d-diffusion-model-for-semi-1","title":"Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection","date":"2023-12-05","arxiv_id":"2312.02966","repositories_listed":1,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":1,"n_instrument":4,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":8,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 4 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/diffusion-ss3d-diffusion-model-for-semi-1#ran","syntology_url":"https://syntology.ai/paper/2312.02966","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.02966"}},"official":{"repos":["luluho1208/diffusion-ss3d"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/bevnext-reviving-dense-bev-frameworks-for-3d","slug":"bevnext-reviving-dense-bev-frameworks-for-3d","title":"BEVNeXt: Reviving Dense BEV Frameworks for 3D Object Detection","date":"2023-12-04","arxiv_id":"2312.01696","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bevnext-reviving-dense-bev-frameworks-for-3d#ran","syntology_url":"https://syntology.ai/paper/2312.01696","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.01696"}},"official":{"repos":["woxihuanjiangguo/bevnext"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/flow-based-feature-fusion-for-vehicle-1","slug":"flow-based-feature-fusion-for-vehicle-1","title":"Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection","date":"2023-11-03","arxiv_id":"2311.01682","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/flow-based-feature-fusion-for-vehicle-1#ran","syntology_url":"https://syntology.ai/paper/2311.01682","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01682"}},"official":{"repos":["haibao-yu/ffnet-vic3d"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/leveraging-vision-centric-multi-modal-1","slug":"leveraging-vision-centric-multi-modal-1","title":"Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection","date":"2023-10-24","arxiv_id":"2310.15670","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/leveraging-vision-centric-multi-modal-1#ran","syntology_url":"https://syntology.ai/paper/2310.15670","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.15670"}},"official":{"repos":["opendrivelab/birds-eye-view-perception"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/dual-radar-a-multi-modal-dataset-with-dual-4d","slug":"dual-radar-a-multi-modal-dataset-with-dual-4d","title":"Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous Driving","date":"2023-10-11","arxiv_id":"2310.07602","repositories_listed":1,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":1,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/dual-radar-a-multi-modal-dataset-with-dual-4d#ran","syntology_url":"https://syntology.ai/paper/2310.07602","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.07602"}},"official":{"repos":["adept-thu/dual-radar"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/uni3detr-unified-3d-detection-transformer-1","slug":"uni3detr-unified-3d-detection-transformer-1","title":"Uni3DETR: Unified 3D Detection Transformer","date":"2023-10-09","arxiv_id":"2310.05699","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/uni3detr-unified-3d-detection-transformer-1#ran","syntology_url":"https://syntology.ai/paper/2310.05699","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05699"}},"official":{"repos":["zhenyuw16/uni3detr"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/magicdrive-street-view-generation-with","slug":"magicdrive-street-view-generation-with","title":"MagicDrive: Street View Generation with Diverse 3D Geometry Control","date":"2023-10-04","arxiv_id":"2310.02601","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/magicdrive-street-view-generation-with#ran","syntology_url":"https://syntology.ai/paper/2310.02601","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.02601"}},"official":null}},{"url":"/paper/see-beyond-seeing-robust-3d-object-detection","slug":"see-beyond-seeing-robust-3d-object-detection","title":"Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature Augmentation","date":"2023-09-29","arxiv_id":"2309.17336","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/see-beyond-seeing-robust-3d-object-detection#ran","syntology_url":"https://syntology.ai/paper/2309.17336","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.17336"}},"official":{"repos":["djning/see_beyond_seeing"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/distillbev-boosting-multi-camera-3d-object","slug":"distillbev-boosting-multi-camera-3d-object","title":"DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation","date":"2023-09-26","arxiv_id":"2309.15109","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/distillbev-boosting-multi-camera-3d-object#ran","syntology_url":"https://syntology.ai/paper/2309.15109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15109"}},"official":{"repos":["qcraftai/distill-bev"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/unibev-multi-modal-3d-object-detection-with","slug":"unibev-multi-modal-3d-object-detection-with","title":"UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities","date":"2023-09-25","arxiv_id":"2309.14516","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/unibev-multi-modal-3d-object-detection-with#ran","syntology_url":"https://syntology.ai/paper/2309.14516","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.14516"}},"official":{"repos":["tudelft-iv/unibev"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/shape-anchor-guided-holistic-indoor-scene","slug":"shape-anchor-guided-holistic-indoor-scene","title":"Shape Anchor Guided Holistic Indoor Scene Understanding","date":"2023-09-20","arxiv_id":"2309.11133","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/shape-anchor-guided-holistic-indoor-scene#ran","syntology_url":"https://syntology.ai/paper/2309.11133","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.11133"}},"official":{"repos":["Geo-Tell/AncRec"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/mononerd-nerf-like-representations-for","slug":"mononerd-nerf-like-representations-for","title":"MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection","date":"2023-08-18","arxiv_id":"2308.09421","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/mononerd-nerf-like-representations-for#ran","syntology_url":"https://syntology.ai/paper/2308.09421","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09421"}},"official":{"repos":["cskkxjk/mononerd"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/far3d-expanding-the-horizon-for-surround-view","slug":"far3d-expanding-the-horizon-for-surround-view","title":"Far3D: Expanding the Horizon for Surround-view 3D Object Detection","date":"2023-08-18","arxiv_id":"2308.09616","repositories_listed":1,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":8,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/far3d-expanding-the-horizon-for-surround-view#ran","syntology_url":"https://syntology.ai/paper/2308.09616","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09616"}},"official":{"repos":["megvii-research/far3d"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/imgeonet-image-induced-geometry-aware-voxel","slug":"imgeonet-image-induced-geometry-aware-voxel","title":"ImGeoNet: Image-induced Geometry-aware Voxel Representation for Multi-view 3D Object Detection","date":"2023-08-17","arxiv_id":"2308.09098","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/imgeonet-image-induced-geometry-aware-voxel#ran","syntology_url":"https://syntology.ai/paper/2308.09098","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09098"}},"official":{"repos":["ttaoREtw/ImGeoNet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/unitr-a-unified-and-efficient-multi-modal","slug":"unitr-a-unified-and-efficient-multi-modal","title":"UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation","date":"2023-08-15","arxiv_id":"2308.07732","repositories_listed":3,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unitr-a-unified-and-efficient-multi-modal#ran","syntology_url":"https://syntology.ai/paper/2308.07732","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.07732"}},"official":{"repos":["haiyang-w/unitr"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/partner-level-up-the-polar-representation-for","slug":"partner-level-up-the-polar-representation-for","title":"PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection","date":"2023-08-08","arxiv_id":"2308.03982","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/partner-level-up-the-polar-representation-for#ran","syntology_url":"https://syntology.ai/paper/2308.03982","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.03982"}},"official":{"repos":["fudan-zvg/partner"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/v-detr-detr-with-vertex-relative-position","slug":"v-detr-detr-with-vertex-relative-position","title":"V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection","date":"2023-08-08","arxiv_id":"2308.04409","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/v-detr-detr-with-vertex-relative-position#ran","syntology_url":"https://syntology.ai/paper/2308.04409","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.04409"}},"official":{"repos":["yichaoshen-ms/v-detr"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-det-learning-geometry-aware-volumetric","slug":"nerf-det-learning-geometry-aware-volumetric","title":"NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection","date":"2023-07-27","arxiv_id":"2307.14620","repositories_listed":3,"syntology":{"n":3,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/nerf-det-learning-geometry-aware-volumetric#ran","syntology_url":"https://syntology.ai/paper/2307.14620","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.14620"}},"official":{"repos":["facebookresearch/nerf-det","open-mmlab/mmdetection3d"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/spatio-temporal-domain-awareness-for-multi","slug":"spatio-temporal-domain-awareness-for-multi","title":"Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perception","date":"2023-07-26","arxiv_id":"2307.13929","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/spatio-temporal-domain-awareness-for-multi#ran","syntology_url":"https://syntology.ai/paper/2307.13929","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.13929"}},"official":null}},{"url":"/paper/pg-rcnn-semantic-surface-point-generation-for","slug":"pg-rcnn-semantic-surface-point-generation-for","title":"PG-RCNN: Semantic Surface Point Generation for 3D Object Detection","date":"2023-07-24","arxiv_id":"2307.12637","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pg-rcnn-semantic-surface-point-generation-for#ran","syntology_url":"https://syntology.ai/paper/2307.12637","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.12637"}},"official":{"repos":["quotation2520/pg-rcnn"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/core-cooperative-reconstruction-for-multi","slug":"core-cooperative-reconstruction-for-multi","title":"CORE: Cooperative Reconstruction for Multi-Agent Perception","date":"2023-07-21","arxiv_id":"2307.11514","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/core-cooperative-reconstruction-for-multi#ran","syntology_url":"https://syntology.ai/paper/2307.11514","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.11514"}},"official":{"repos":["zllxot/core"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/revisiting-domain-adaptive-3d-object","slug":"revisiting-domain-adaptive-3d-object","title":"Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling","date":"2023-07-16","arxiv_id":"2307.07944","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/revisiting-domain-adaptive-3d-object#ran","syntology_url":"https://syntology.ai/paper/2307.07944","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07944"}},"official":{"repos":["zhuoxiao-chen/redb-da-3ddet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/spatial-temporal-enhanced-transformer-towards","slug":"spatial-temporal-enhanced-transformer-towards","title":"Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object Detection","date":"2023-07-01","arxiv_id":"2307.00347","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/spatial-temporal-enhanced-transformer-towards#ran","syntology_url":"https://syntology.ai/paper/2307.00347","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.00347"}},"official":{"repos":["eaphan/stemd"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/tame-a-wild-camera-in-the-wild-monocular-1","slug":"tame-a-wild-camera-in-the-wild-monocular-1","title":"Tame a Wild Camera: In-the-Wild Monocular Camera Calibration","date":"2023-06-19","arxiv_id":"2306.10988","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/tame-a-wild-camera-in-the-wild-monocular-1#ran","syntology_url":"https://syntology.ai/paper/2306.10988","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.10988"}},"official":{"repos":["shngjz/wildcamera"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/detzero-rethinking-offboard-3d-object","slug":"detzero-rethinking-offboard-3d-object","title":"DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds","date":"2023-06-09","arxiv_id":"2306.06023","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/detzero-rethinking-offboard-3d-object#ran","syntology_url":"https://syntology.ai/paper/2306.06023","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.06023"}},"official":{"repos":["pjlab-adg/detzero"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/modar-using-motion-forecasting-for-3d-object-1","slug":"modar-using-motion-forecasting-for-3d-object-1","title":"MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences","date":"2023-06-05","arxiv_id":"2306.03206","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/modar-using-motion-forecasting-for-3d-object-1#ran","syntology_url":"https://syntology.ai/paper/2306.03206","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.03206"}},"official":null}},{"url":"/paper/octformer-octree-based-transformers-for-3d","slug":"octformer-octree-based-transformers-for-3d","title":"OctFormer: Octree-based Transformers for 3D Point Clouds","date":"2023-05-04","arxiv_id":"2305.03045","repositories_listed":4,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":3,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/octformer-octree-based-transformers-for-3d#ran","syntology_url":"https://syntology.ai/paper/2305.03045","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.03045"}},"official":{"repos":["octree-nn/octformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/fully-sparse-fusion-for-3d-object-detection","slug":"fully-sparse-fusion-for-3d-object-detection","title":"Fully Sparse Fusion for 3D Object Detection","date":"2023-04-24","arxiv_id":"2304.12310","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/fully-sparse-fusion-for-3d-object-detection#ran","syntology_url":"https://syntology.ai/paper/2304.12310","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.12310"}},"official":{"repos":["bravegroup/fullysparsefusion"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/once-detected-never-lost-surpassing-human","slug":"once-detected-never-lost-surpassing-human","title":"Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection","date":"2023-04-24","arxiv_id":"2304.12315","repositories_listed":2,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/once-detected-never-lost-surpassing-human#ran","syntology_url":"https://syntology.ai/paper/2304.12315","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.12315"}},"official":{"repos":["tusen-ai/sst"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/density-insensitive-unsupervised-domain","slug":"density-insensitive-unsupervised-domain","title":"Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection","date":"2023-04-19","arxiv_id":"2304.09446","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/density-insensitive-unsupervised-domain#ran","syntology_url":"https://syntology.ai/paper/2304.09446","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.09446"}},"official":{"repos":["woodwindhu/dts"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/swin3d-a-pretrained-transformer-backbone-for","slug":"swin3d-a-pretrained-transformer-backbone-for","title":"Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding","date":"2023-04-14","arxiv_id":"2304.06906","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/swin3d-a-pretrained-transformer-backbone-for#ran","syntology_url":"https://syntology.ai/paper/2304.06906","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.06906"}},"official":{"repos":["microsoft/swin3d"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/curricular-object-manipulation-in-lidar-based","slug":"curricular-object-manipulation-in-lidar-based","title":"Curricular Object Manipulation in LiDAR-based Object Detection","date":"2023-04-09","arxiv_id":"2304.04248","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/curricular-object-manipulation-in-lidar-based#ran","syntology_url":"https://syntology.ai/paper/2304.04248","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.04248"}},"official":{"repos":["zzy816/com"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/geometric-aware-pretraining-for-vision","slug":"geometric-aware-pretraining-for-vision","title":"Geometric-aware Pretraining for Vision-centric 3D Object Detection","date":"2023-04-06","arxiv_id":"2304.03105","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/geometric-aware-pretraining-for-vision#ran","syntology_url":"https://syntology.ai/paper/2304.03105","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.03105"}},"official":{"repos":["opendrivelab/bevperception-survey-recipe"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/crn-camera-radar-net-for-accurate-robust","slug":"crn-camera-radar-net-for-accurate-robust","title":"CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception","date":"2023-04-03","arxiv_id":"2304.00670","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/crn-camera-radar-net-for-accurate-robust#ran","syntology_url":"https://syntology.ai/paper/2304.00670","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.00670"}},"official":{"repos":["youngskkim/CRN"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/open-vocabulary-point-cloud-object-detection","slug":"open-vocabulary-point-cloud-object-detection","title":"Open-Vocabulary Point-Cloud Object Detection without 3D Annotation","date":"2023-04-03","arxiv_id":"2304.00788","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/open-vocabulary-point-cloud-object-detection#ran","syntology_url":"https://syntology.ai/paper/2304.00788","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.00788"}},"official":{"repos":["lyhdet/ov-3det"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/temporal-enhanced-training-of-multi-view-3d","slug":"temporal-enhanced-training-of-multi-view-3d","title":"Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction","date":"2023-04-03","arxiv_id":"2304.00967","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/temporal-enhanced-training-of-multi-view-3d#ran","syntology_url":"https://syntology.ai/paper/2304.00967","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.00967"}},"official":{"repos":["sense-x/hop"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/voxelformer-bird-s-eye-view-feature","slug":"voxelformer-bird-s-eye-view-feature","title":"VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection","date":"2023-04-03","arxiv_id":"2304.01054","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/voxelformer-bird-s-eye-view-feature#ran","syntology_url":"https://syntology.ai/paper/2304.01054","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.01054"}},"official":{"repos":["lizhuoling/voxelformer-public"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/ea-bev-edge-aware-bird-s-eye-view-projector","slug":"ea-bev-edge-aware-bird-s-eye-view-projector","title":"EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detection","date":"2023-03-31","arxiv_id":"2303.17895","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ea-bev-edge-aware-bird-s-eye-view-projector#ran","syntology_url":"https://syntology.ai/paper/2303.17895","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.17895"}},"official":{"repos":["hht1996ok/ea-bev"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/understanding-the-robustness-of-3d-object","slug":"understanding-the-robustness-of-3d-object","title":"Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving","date":"2023-03-30","arxiv_id":"2303.17297","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/understanding-the-robustness-of-3d-object#ran","syntology_url":"https://syntology.ai/paper/2303.17297","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.17297"}},"official":{"repos":["zzj403/BEV_Robust"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/bevsimdet-simulated-multi-modal-distillation","slug":"bevsimdet-simulated-multi-modal-distillation","title":"SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection","date":"2023-03-29","arxiv_id":"2303.16818","repositories_listed":2,"syntology":{"n":10,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":3,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bevsimdet-simulated-multi-modal-distillation#ran","syntology_url":"https://syntology.ai/paper/2303.16818","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.16818"}},"official":{"repos":["vitae-transformer/bevsimdet","vitae-transformer/simdistill"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/link-linear-kernel-for-lidar-based-3d","slug":"link-linear-kernel-for-lidar-based-3d","title":"LinK: Linear Kernel for LiDAR-based 3D Perception","date":"2023-03-28","arxiv_id":"2303.16094","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":3,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/link-linear-kernel-for-lidar-based-3d#ran","syntology_url":"https://syntology.ai/paper/2303.16094","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.16094"}},"official":{"repos":["mcg-nju/link"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unidistill-a-universal-cross-modality","slug":"unidistill-a-universal-cross-modality","title":"UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View","date":"2023-03-27","arxiv_id":"2303.15083","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/unidistill-a-universal-cross-modality#ran","syntology_url":"https://syntology.ai/paper/2303.15083","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.15083"}},"official":{"repos":["megvii-research/cvpr2023-unidistill"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}}],"record_sha256":"1a535a023088509a03995056a4f856cf9e83f128626b12d60e38750f2f622d64","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}