{"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/object/papers/3","list_of":"/task/object","task":"Object","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":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":107,"rows_per_page":100,"rows":[201,300],"of":10696,"counts":{"archive_papers_tagged":10696,"with_a_code_link":3979,"where_syntology_ran_a_sample":1043,"not_listed_spam_title":0,"listed":10696,"listed_where_code_ran":1043,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":919,"every_run_a_failure_of_syntologys_instrument":124,"listed_with_a_run_with_no_instrument_failure":919,"listed_every_run_a_failure_of_syntologys_instrument":124,"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/object","prev":"/task/object/papers/2","next":"/task/object/papers/4","papers":[{"url":"/paper/yolo-world-real-time-open-vocabulary-object","slug":"yolo-world-real-time-open-vocabulary-object","title":"YOLO-World: Real-Time Open-Vocabulary Object Detection","date":"2024-01-30","arxiv_id":"2401.17270","repositories_listed":3,"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/yolo-world-real-time-open-vocabulary-object#ran","syntology_url":"https://syntology.ai/paper/2401.17270","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.17270"}},"official":{"repos":["ailab-cvc/yolo-world"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/deco-query-based-end-to-end-object-detection","slug":"deco-query-based-end-to-end-object-detection","title":"DECO: Query-Based End-to-End Object Detection with ConvNets","date":"2023-12-21","arxiv_id":"2312.13735","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"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 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/deco-query-based-end-to-end-object-detection#ran","syntology_url":"https://syntology.ai/paper/2312.13735","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.13735"}},"official":{"repos":["xinghaochen/DECO","mindspore-lab/models"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/rotation-invariant-transformer-for-1","slug":"rotation-invariant-transformer-for-1","title":"Rotation Invariant Transformer for Recognizing Object in UAVs","date":"2023-11-05","arxiv_id":"2311.02559","repositories_listed":3,"syntology":null},{"url":"/paper/towards-robust-robot-3d-perception-in-urban","slug":"towards-robust-robot-3d-perception-in-urban","title":"Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset","date":"2023-09-24","arxiv_id":"2309.13549","repositories_listed":3,"syntology":null},{"url":"/paper/towards-subcentimeter-accuracy-digital-twin","slug":"towards-subcentimeter-accuracy-digital-twin","title":"Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset","date":"2023-09-24","arxiv_id":"2309.13570","repositories_listed":3,"syntology":null},{"url":"/paper/pointllm-empowering-large-language-models-to","slug":"pointllm-empowering-large-language-models-to","title":"PointLLM: Empowering Large Language Models to Understand Point Clouds","date":"2023-08-31","arxiv_id":"2308.16911","repositories_listed":3,"syntology":null},{"url":"/paper/pe-yolo-pyramid-enhancement-network-for-dark","slug":"pe-yolo-pyramid-enhancement-network-for-dark","title":"PE-YOLO: Pyramid Enhancement Network for Dark Object Detection","date":"2023-07-20","arxiv_id":"2307.10953","repositories_listed":3,"syntology":null},{"url":"/paper/semi-detr-semi-supervised-object-detection-1","slug":"semi-detr-semi-supervised-object-detection-1","title":"Semi-DETR: Semi-Supervised Object Detection with Detection Transformers","date":"2023-07-16","arxiv_id":"2307.08095","repositories_listed":3,"syntology":null},{"url":"/paper/scaling-open-vocabulary-object-detection-1","slug":"scaling-open-vocabulary-object-detection-1","title":"Scaling Open-Vocabulary Object Detection","date":"2023-06-16","arxiv_id":"2306.09683","repositories_listed":3,"syntology":null},{"url":"/paper/deep-oc-sort-multi-pedestrian-tracking-by","slug":"deep-oc-sort-multi-pedestrian-tracking-by","title":"Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification","date":"2023-02-23","arxiv_id":"2302.11813","repositories_listed":3,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"8 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; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/deep-oc-sort-multi-pedestrian-tracking-by#ran","syntology_url":"https://syntology.ai/paper/2302.11813","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.11813"}},"official":{"repos":["gerardmaggiolino/deep-oc-sort"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/digital-twin-tracking-dataset-dttd-a-new-rgb","slug":"digital-twin-tracking-dataset-dttd-a-new-rgb","title":"Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications","date":"2023-02-12","arxiv_id":"2302.05991","repositories_listed":3,"syntology":null},{"url":"/paper/sgdraw-scene-graph-drawing-interface-using","slug":"sgdraw-scene-graph-drawing-interface-using","title":"SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation","date":"2022-11-30","arxiv_id":"2211.16697","repositories_listed":3,"syntology":null},{"url":"/paper/diffusiondet-diffusion-model-for-object","slug":"diffusiondet-diffusion-model-for-object","title":"DiffusionDet: Diffusion Model for Object Detection","date":"2022-11-17","arxiv_id":"2211.09788","repositories_listed":3,"syntology":null},{"url":"/paper/harmonizing-the-object-recognition-strategies","slug":"harmonizing-the-object-recognition-strategies","title":"Harmonizing the object recognition strategies of deep neural networks with humans","date":"2022-11-08","arxiv_id":"2211.04533","repositories_listed":3,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/harmonizing-the-object-recognition-strategies#ran","syntology_url":"https://syntology.ai/paper/2211.04533","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.04533"}},"official":null}},{"url":"/paper/h2rbox-horizonal-box-annotation-is-all-you","slug":"h2rbox-horizonal-box-annotation-is-all-you","title":"H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection","date":"2022-10-13","arxiv_id":"2210.06742","repositories_listed":3,"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/h2rbox-horizonal-box-annotation-is-all-you#ran","syntology_url":"https://syntology.ai/paper/2210.06742","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.06742"}},"official":{"repos":["yangxue0827/h2rbox-jittor","yangxue0827/h2rbox-mmrotate"],"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/eda-explicit-text-decoupling-and-dense","slug":"eda-explicit-text-decoupling-and-dense","title":"EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual Grounding","date":"2022-09-29","arxiv_id":"2209.14941","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"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) · 0 unverified","sample_list":"/paper/eda-explicit-text-decoupling-and-dense#ran","syntology_url":"https://syntology.ai/paper/2209.14941","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.14941"}},"official":{"repos":["yanmin-wu/eda"],"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/epic-kitchens-visor-benchmark-video","slug":"epic-kitchens-visor-benchmark-video","title":"EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations","date":"2022-09-26","arxiv_id":"2209.13064","repositories_listed":3,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":2,"n_instrument":5,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/epic-kitchens-visor-benchmark-video#ran","syntology_url":"https://syntology.ai/paper/2209.13064","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.13064"}},"official":{"repos":["epic-kitchens/visor-hos","epic-kitchens/visor-vos","epic-kitchens/visor-wdtcf"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/point-to-box-network-for-accurate-object","slug":"point-to-box-network-for-accurate-object","title":"Point-to-Box Network for Accurate Object Detection via Single Point Supervision","date":"2022-07-14","arxiv_id":"2207.06827","repositories_listed":3,"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/point-to-box-network-for-accurate-object#ran","syntology_url":"https://syntology.ai/paper/2207.06827","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.06827"}},"official":{"repos":["ucas-vg/p2bnet"],"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/fewsol-a-dataset-for-few-shot-object-learning","slug":"fewsol-a-dataset-for-few-shot-object-learning","title":"FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments","date":"2022-07-06","arxiv_id":"2207.03333","repositories_listed":3,"syntology":null},{"url":"/paper/small-object-detection-via-pixel-level","slug":"small-object-detection-via-pixel-level","title":"Small Object Detection via Pixel Level Balancing With Applications to Blood Cell Detection","date":"2022-06-17","arxiv_id":null,"repositories_listed":3,"syntology":null},{"url":"/paper/label-matching-semi-supervised-object-1","slug":"label-matching-semi-supervised-object-1","title":"Label Matching Semi-Supervised Object Detection","date":"2022-06-14","arxiv_id":"2206.06608","repositories_listed":3,"syntology":null},{"url":"/paper/gconet-a-stronger-group-collaborative-co","slug":"gconet-a-stronger-group-collaborative-co","title":"GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector","date":"2022-05-30","arxiv_id":"2205.15469","repositories_listed":3,"syntology":null},{"url":"/paper/integral-migrating-pre-trained-transformer","slug":"integral-migrating-pre-trained-transformer","title":"Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection","date":"2022-05-19","arxiv_id":"2205.09613","repositories_listed":3,"syntology":null},{"url":"/paper/centernet-for-object-detection","slug":"centernet-for-object-detection","title":"CenterNet++ for Object Detection","date":"2022-04-18","arxiv_id":"2204.08394","repositories_listed":3,"syntology":null},{"url":"/paper/gpv-pose-category-level-object-pose","slug":"gpv-pose-category-level-object-pose","title":"GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting","date":"2022-03-15","arxiv_id":"2203.07918","repositories_listed":3,"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/gpv-pose-category-level-object-pose#ran","syntology_url":"https://syntology.ai/paper/2203.07918","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07918"}},"official":{"repos":["lolrudy/gpv_pose"],"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/centersnap-single-shot-multi-object-3d-shape","slug":"centersnap-single-shot-multi-object-3d-shape","title":"CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation","date":"2022-03-03","arxiv_id":"2203.01929","repositories_listed":3,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/centersnap-single-shot-multi-object-3d-shape#ran","syntology_url":"https://syntology.ai/paper/2203.01929","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.01929"}},"official":null}},{"url":"/paper/the-kfiou-loss-for-rotated-object-detection-1","slug":"the-kfiou-loss-for-rotated-object-detection-1","title":"The KFIoU Loss for Rotated Object Detection","date":"2022-01-29","arxiv_id":"2201.12558","repositories_listed":3,"syntology":{"n":7,"n_ran":4,"n_constructed":1,"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 1 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/the-kfiou-loss-for-rotated-object-detection-1#ran","syntology_url":"https://syntology.ai/paper/2201.12558","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.12558"}},"official":{"repos":["Jittor/JDet","yangxue0827/RotationDetection"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/transvod-end-to-end-video-object-detection","slug":"transvod-end-to-end-video-object-detection","title":"TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers","date":"2022-01-13","arxiv_id":"2201.05047","repositories_listed":3,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":3,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":2,"n_pointer_only":3,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/transvod-end-to-end-video-object-detection#ran","syntology_url":"https://syntology.ai/paper/2201.05047","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.05047"}},"official":{"repos":["qianyuzqy/TransVOD_Lite"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["named_in_paper","official"]}}},{"url":"/paper/a-simple-single-scale-vision-transformer-for","slug":"a-simple-single-scale-vision-transformer-for","title":"A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation","date":"2021-12-17","arxiv_id":"2112.09747","repositories_listed":3,"syntology":null},{"url":"/paper/homography-decomposition-networks-for-planar","slug":"homography-decomposition-networks-for-planar","title":"Homography Decomposition Networks for Planar Object Tracking","date":"2021-12-15","arxiv_id":"2112.07909","repositories_listed":3,"syntology":null},{"url":"/paper/dancetrack-multi-object-tracking-in-uniform","slug":"dancetrack-multi-object-tracking-in-uniform","title":"DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion","date":"2021-11-29","arxiv_id":"2111.14690","repositories_listed":3,"syntology":null},{"url":"/paper/conditional-object-centric-learning-from-1","slug":"conditional-object-centric-learning-from-1","title":"Conditional Object-Centric Learning from Video","date":"2021-11-24","arxiv_id":"2111.12594","repositories_listed":3,"syntology":{"n":13,"n_ran":11,"n_constructed":8,"n_ran_checked":11,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":10,"phrase":"11 ran (of which 8 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/conditional-object-centric-learning-from-1#ran","syntology_url":"https://syntology.ai/paper/2111.12594","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12594"}},"official":{"repos":["google-research/slot-attention-video"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/a-normalized-gaussian-wasserstein-distance","slug":"a-normalized-gaussian-wasserstein-distance","title":"A Normalized Gaussian Wasserstein Distance for Tiny Object Detection","date":"2021-10-26","arxiv_id":"2110.13389","repositories_listed":3,"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":2,"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/a-normalized-gaussian-wasserstein-distance#ran","syntology_url":"https://syntology.ai/paper/2110.13389","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.13389"}},"official":{"repos":["jwwangchn/NWD"],"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/efficient-and-high-quality-prehensile","slug":"efficient-and-high-quality-prehensile","title":"Efficient and High-quality Prehensile Rearrangement in Cluttered and Confined Spaces","date":"2021-10-06","arxiv_id":"2110.02814","repositories_listed":3,"syntology":null},{"url":"/paper/tph-yolov5-improved-yolov5-based-on","slug":"tph-yolov5-improved-yolov5-based-on","title":"TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios","date":"2021-08-26","arxiv_id":"2108.11539","repositories_listed":3,"syntology":null},{"url":"/paper/exploring-simple-3d-multi-object-tracking-for","slug":"exploring-simple-3d-multi-object-tracking-for","title":"Exploring Simple 3D Multi-Object Tracking for Autonomous Driving","date":"2021-08-23","arxiv_id":"2108.10312","repositories_listed":3,"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/exploring-simple-3d-multi-object-tracking-for#ran","syntology_url":"https://syntology.ai/paper/2108.10312","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.10312"}},"official":{"repos":["qcraftai/simtrack"],"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/rank-sort-loss-for-object-detection-and","slug":"rank-sort-loss-for-object-detection-and","title":"Rank & Sort Loss for Object Detection and Instance Segmentation","date":"2021-07-24","arxiv_id":"2107.11669","repositories_listed":3,"syntology":null},{"url":"/paper/layercam-exploring-hierarchical-class","slug":"layercam-exploring-hierarchical-class","title":"LayerCAM: Exploring Hierarchical Class Activation Maps for Localization","date":"2021-06-22","arxiv_id":null,"repositories_listed":3,"syntology":null},{"url":"/paper/dynamic-head-unifying-object-detection-heads","slug":"dynamic-head-unifying-object-detection-heads","title":"Dynamic Head: Unifying Object Detection Heads with Attentions","date":"2021-06-15","arxiv_id":"2106.08322","repositories_listed":3,"syntology":{"n":9,"n_ran":8,"n_constructed":5,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dynamic-head-unifying-object-detection-heads#ran","syntology_url":"https://syntology.ai/paper/2106.08322","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.08322"}},"official":{"repos":["microsoft/DynamicHead"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/eagermot-3d-multi-object-tracking-via-sensor","slug":"eagermot-3d-multi-object-tracking-via-sensor","title":"EagerMOT: 3D Multi-Object Tracking via Sensor Fusion","date":"2021-04-29","arxiv_id":"2104.14682","repositories_listed":3,"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/eagermot-3d-multi-object-tracking-via-sensor#ran","syntology_url":"https://syntology.ai/paper/2104.14682","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.14682"}},"official":{"repos":["aleksandrkim61/EagerMOT"],"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/houghnet-integrating-near-and-long-range-1","slug":"houghnet-integrating-near-and-long-range-1","title":"HoughNet: Integrating near and long-range evidence for visual detection","date":"2021-04-14","arxiv_id":"2104.06773","repositories_listed":3,"syntology":null},{"url":"/paper/pointly-supervised-instance-segmentation","slug":"pointly-supervised-instance-segmentation","title":"Pointly-Supervised Instance Segmentation","date":"2021-04-13","arxiv_id":"2104.06404","repositories_listed":3,"syntology":null},{"url":"/paper/multimodal-object-detection-via-bayesian","slug":"multimodal-object-detection-via-bayesian","title":"Multimodal Object Detection via Probabilistic Ensembling","date":"2021-04-07","arxiv_id":"2104.02904","repositories_listed":3,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":6,"n_pointer_only":8,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 2 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/multimodal-object-detection-via-bayesian#ran","syntology_url":"https://syntology.ai/paper/2104.02904","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.02904"}},"official":{"repos":["Jamie725/RGBT-detection"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/objects-are-different-flexible-monocular-3d","slug":"objects-are-different-flexible-monocular-3d","title":"Objects are Different: Flexible Monocular 3D Object Detection","date":"2021-04-06","arxiv_id":"2104.02323","repositories_listed":3,"syntology":{"n":20,"n_ran":14,"n_constructed":1,"n_ran_checked":6,"n_instrument":8,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"phrase":"14 ran (of which 1 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 8 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/objects-are-different-flexible-monocular-3d#ran","syntology_url":"https://syntology.ai/paper/2104.02323","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.02323"}},"official":{"repos":["zhangyp15/MonoFlex"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/robust-and-accurate-object-detection-via","slug":"robust-and-accurate-object-detection-via","title":"Robust and Accurate Object Detection via Adversarial Learning","date":"2021-03-23","arxiv_id":"2103.13886","repositories_listed":3,"syntology":null},{"url":"/paper/uncertainty-aware-unsupervised-domain","slug":"uncertainty-aware-unsupervised-domain","title":"Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection","date":"2021-02-27","arxiv_id":"2103.00236","repositories_listed":3,"syntology":null},{"url":"/paper/a-comparative-analysis-of-object-detection","slug":"a-comparative-analysis-of-object-detection","title":"A Comparative Analysis of Object Detection Metrics with a Companion Open-Source Toolkit","date":"2021-01-25","arxiv_id":null,"repositories_listed":3,"syntology":null},{"url":"/paper/salient-object-detection-via-integrity","slug":"salient-object-detection-via-integrity","title":"Salient Object Detection via Integrity Learning","date":"2021-01-19","arxiv_id":"2101.07663","repositories_listed":3,"syntology":null},{"url":"/paper/estimating-and-evaluating-regression","slug":"estimating-and-evaluating-regression","title":"Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors","date":"2021-01-13","arxiv_id":"2101.05036","repositories_listed":3,"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/estimating-and-evaluating-regression#ran","syntology_url":"https://syntology.ai/paper/2101.05036","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2101.05036"}},"official":{"repos":["asharakeh/probdet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/yolobile-real-time-object-detection-on-mobile","slug":"yolobile-real-time-object-detection-on-mobile","title":"YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design","date":"2020-09-12","arxiv_id":"2009.05697","repositories_listed":3,"syntology":null},{"url":"/paper/align-deep-features-for-oriented-object","slug":"align-deep-features-for-oriented-object","title":"Align Deep Features for Oriented Object Detection","date":"2020-08-21","arxiv_id":"2008.09397","repositories_listed":3,"syntology":null},{"url":"/paper/simultaneous-detection-and-tracking-with","slug":"simultaneous-detection-and-tracking-with","title":"Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking","date":"2020-08-20","arxiv_id":"2008.08826","repositories_listed":3,"syntology":null},{"url":"/paper/objectnav-revisited-on-evaluation-of-embodied","slug":"objectnav-revisited-on-evaluation-of-embodied","title":"ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects","date":"2020-06-23","arxiv_id":"2006.13171","repositories_listed":3,"syntology":null},{"url":"/paper/quasi-dense-instance-similarity-learning","slug":"quasi-dense-instance-similarity-learning","title":"Quasi-Dense Similarity Learning for Multiple Object Tracking","date":"2020-06-11","arxiv_id":"2006.06664","repositories_listed":3,"syntology":null},{"url":"/paper/object-detection-in-the-dct-domain-is","slug":"object-detection-in-the-dct-domain-is","title":"Object Detection in the DCT Domain: is Luminance the Solution?","date":"2020-06-10","arxiv_id":"2006.05732","repositories_listed":3,"syntology":null},{"url":"/paper/self-paced-contrastive-learning-with-hybrid","slug":"self-paced-contrastive-learning-with-hybrid","title":"Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID","date":"2020-06-04","arxiv_id":"2006.02713","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":2,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/self-paced-contrastive-learning-with-hybrid#ran","syntology_url":"https://syntology.ai/paper/2006.02713","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.02713"}},"official":{"repos":["yxgeee/SpCL"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-implicit-surface-light-fields","slug":"learning-implicit-surface-light-fields","title":"Learning Implicit Surface Light Fields","date":"2020-03-27","arxiv_id":"2003.12406","repositories_listed":3,"syntology":null},{"url":"/paper/learning-layout-and-style-reconfigurable-gans","slug":"learning-layout-and-style-reconfigurable-gans","title":"Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis","date":"2020-03-25","arxiv_id":"2003.11571","repositories_listed":3,"syntology":null},{"url":"/paper/first-order-motion-model-for-image-animation-1","slug":"first-order-motion-model-for-image-animation-1","title":"First Order Motion Model for Image Animation","date":"2020-02-29","arxiv_id":"2003.00196","repositories_listed":3,"syntology":{"n":10,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":7,"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) · 7 unverified","sample_list":"/paper/first-order-motion-model-for-image-animation-1#ran","syntology_url":"https://syntology.ai/paper/2003.00196","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.00196"}},"official":{"repos":["AliaksandrSiarohin/first-order-model"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/smoke-single-stage-monocular-3d-object","slug":"smoke-single-stage-monocular-3d-object","title":"SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation","date":"2020-02-24","arxiv_id":"2002.10111","repositories_listed":3,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"phrase":"8 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/smoke-single-stage-monocular-3d-object#ran","syntology_url":"https://syntology.ai/paper/2002.10111","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.10111"}},"official":{"repos":["lzccccc/SMOKE"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/probabilistic-3d-multi-object-tracking-for","slug":"probabilistic-3d-multi-object-tracking-for","title":"Probabilistic 3D Multi-Object Tracking for Autonomous Driving","date":"2020-01-16","arxiv_id":"2001.05673","repositories_listed":3,"syntology":null},{"url":"/paper/hybridpose-6d-object-pose-estimation-under","slug":"hybridpose-6d-object-pose-estimation-under","title":"HybridPose: 6D Object Pose Estimation under Hybrid Representations","date":"2020-01-07","arxiv_id":"2001.01869","repositories_listed":3,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":5,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 5 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/hybridpose-6d-object-pose-estimation-under#ran","syntology_url":"https://syntology.ai/paper/2001.01869","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2001.01869"}},"official":{"repos":["chensong1995/HybridPose"],"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":["listed","official"]}}},{"url":"/paper/scanrefer-3d-object-localization-in-rgb-d","slug":"scanrefer-3d-object-localization-in-rgb-d","title":"ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language","date":"2019-12-18","arxiv_id":"1912.08830","repositories_listed":3,"syntology":null},{"url":"/paper/side-aware-boundary-localization-for-more","slug":"side-aware-boundary-localization-for-more","title":"Side-Aware Boundary Localization for More Precise Object Detection","date":"2019-12-09","arxiv_id":"1912.04260","repositories_listed":3,"syntology":null},{"url":"/paper/multiple-anchor-learning-for-visual-object","slug":"multiple-anchor-learning-for-visual-object","title":"Multiple Anchor Learning for Visual Object Detection","date":"2019-12-04","arxiv_id":"1912.02252","repositories_listed":3,"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":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) · 3 unverified","sample_list":"/paper/multiple-anchor-learning-for-visual-object#ran","syntology_url":"https://syntology.ai/paper/1912.02252","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.02252"}},"official":null}},{"url":"/paper/cagnet-content-aware-guidance-for-salient","slug":"cagnet-content-aware-guidance-for-salient","title":"CAGNet: Content-Aware Guidance for Salient Object Detection","date":"2019-11-29","arxiv_id":"1911.13168","repositories_listed":3,"syntology":null},{"url":"/paper/mixture-model-based-bounding-box-density","slug":"mixture-model-based-bounding-box-density","title":"Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image","date":"2019-11-28","arxiv_id":"1911.12721","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"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, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mixture-model-based-bounding-box-density#ran","syntology_url":"https://syntology.ai/paper/1911.12721","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.12721"}},"official":{"repos":["yoojy31/mdod"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/contrastive-learning-of-structured-world-1","slug":"contrastive-learning-of-structured-world-1","title":"Contrastive Learning of Structured World Models","date":"2019-11-27","arxiv_id":"1911.12247","repositories_listed":3,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/contrastive-learning-of-structured-world-1#ran","syntology_url":"https://syntology.ai/paper/1911.12247","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.12247"}},"official":{"repos":["tkipf/c-swm"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/instance-shadow-detection","slug":"instance-shadow-detection","title":"Instance Shadow Detection","date":"2019-11-16","arxiv_id":"1911.07034","repositories_listed":3,"syntology":null},{"url":"/paper/cylindrical-shape-decomposition-algorithm-for","slug":"cylindrical-shape-decomposition-algorithm-for","title":"Cylindrical Shape Decomposition for 3D Segmentation of Tubular Objects","date":"2019-11-01","arxiv_id":"1911.00571","repositories_listed":3,"syntology":null},{"url":"/paper/egnetedge-guidance-network-for-salient-object","slug":"egnetedge-guidance-network-for-salient-object","title":"EGNet:Edge Guidance Network for Salient Object Detection","date":"2019-08-22","arxiv_id":"1908.08297","repositories_listed":3,"syntology":null},{"url":"/paper/revisiting-point-cloud-classification-a-new","slug":"revisiting-point-cloud-classification-a-new","title":"Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data","date":"2019-08-13","arxiv_id":"1908.04616","repositories_listed":3,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"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) · 2 unverified","sample_list":"/paper/revisiting-point-cloud-classification-a-new#ran","syntology_url":"https://syntology.ai/paper/1908.04616","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.04616"}},"official":{"repos":["hkust-vgd/scanobjectnn"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/lvis-a-dataset-for-large-vocabulary-instance-1","slug":"lvis-a-dataset-for-large-vocabulary-instance-1","title":"LVIS: A Dataset for Large Vocabulary Instance Segmentation","date":"2019-08-08","arxiv_id":"1908.03195","repositories_listed":3,"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/lvis-a-dataset-for-large-vocabulary-instance-1#ran","syntology_url":"https://syntology.ai/paper/1908.03195","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.03195"}},"official":null}},{"url":"/paper/few-shot-object-detection-with-attention-rpn","slug":"few-shot-object-detection-with-attention-rpn","title":"Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector","date":"2019-08-06","arxiv_id":"1908.01998","repositories_listed":3,"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":2,"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/few-shot-object-detection-with-attention-rpn#ran","syntology_url":"https://syntology.ai/paper/1908.01998","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.01998"}},"official":{"repos":["fanq15/FewX"],"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/nas-fcos-fast-neural-architecture-search-for","slug":"nas-fcos-fast-neural-architecture-search-for","title":"NAS-FCOS: Fast Neural Architecture Search for Object Detection","date":"2019-06-11","arxiv_id":"1906.04423","repositories_listed":3,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/nas-fcos-fast-neural-architecture-search-for#ran","syntology_url":"https://syntology.ai/paper/1906.04423","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.04423"}},"official":null}},{"url":"/paper/distilling-object-detectors-with-fine-grained-1","slug":"distilling-object-detectors-with-fine-grained-1","title":"Distilling Object Detectors with Fine-grained Feature Imitation","date":"2019-06-09","arxiv_id":"1906.03609","repositories_listed":3,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/distilling-object-detectors-with-fine-grained-1#ran","syntology_url":"https://syntology.ai/paper/1906.03609","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.03609"}},"official":{"repos":["twangnh/Distilling-Object-Detectors"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/basnet-boundary-aware-salient-object","slug":"basnet-boundary-aware-salient-object","title":"BASNet: Boundary-Aware Salient Object Detection","date":"2019-06-01","arxiv_id":null,"repositories_listed":3,"syntology":null},{"url":"/paper/isaid-a-large-scale-dataset-for-instance","slug":"isaid-a-large-scale-dataset-for-instance","title":"iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images","date":"2019-05-30","arxiv_id":"1905.12886","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"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) · 0 unverified","sample_list":"/paper/isaid-a-large-scale-dataset-for-instance#ran","syntology_url":"https://syntology.ai/paper/1905.12886","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.12886"}},"official":{"repos":["CAPTAIN-WHU/iSAID_Devkit"],"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/190503633","slug":"190503633","title":"Intra-frame Object Tracking by Deblatting","date":"2019-05-09","arxiv_id":"1905.03633","repositories_listed":3,"syntology":{"n":3,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 3 unverified","sample_list":"/paper/190503633#ran","syntology_url":"https://syntology.ai/paper/1905.03633","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.03633"}},"official":{"repos":["rozumden/deblatting_python"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"url":"/paper/learning-joint-reconstruction-of-hands-and","slug":"learning-joint-reconstruction-of-hands-and","title":"Learning joint reconstruction of hands and manipulated objects","date":"2019-04-11","arxiv_id":"1904.05767","repositories_listed":3,"syntology":null},{"url":"/paper/video-object-segmentation-using-space-time","slug":"video-object-segmentation-using-space-time","title":"Video Object Segmentation using Space-Time Memory Networks","date":"2019-04-01","arxiv_id":"1904.00607","repositories_listed":3,"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/video-object-segmentation-using-space-time#ran","syntology_url":"https://syntology.ai/paper/1904.00607","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.00607"}},"official":null}},{"url":"/paper/thundernet-towards-real-time-generic-object","slug":"thundernet-towards-real-time-generic-object","title":"ThunderNet: Towards Real-time Generic Object Detection","date":"2019-03-28","arxiv_id":"1903.11752","repositories_listed":3,"syntology":null},{"url":"/paper/feelvos-fast-end-to-end-embedding-learning","slug":"feelvos-fast-end-to-end-embedding-learning","title":"FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation","date":"2019-02-25","arxiv_id":"1902.09513","repositories_listed":3,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":1,"phrase":"9 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/feelvos-fast-end-to-end-embedding-learning#ran","syntology_url":"https://syntology.ai/paper/1902.09513","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1902.09513"}},"official":{"repos":["tensorflow/models"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/deepball-deep-neural-network-ball-detector","slug":"deepball-deep-neural-network-ball-detector","title":"DeepBall: Deep Neural-Network Ball Detector","date":"2019-02-19","arxiv_id":"1902.07304","repositories_listed":3,"syntology":null},{"url":"/paper/multigrain-a-unified-image-embedding-for","slug":"multigrain-a-unified-image-embedding-for","title":"MultiGrain: a unified image embedding for classes and instances","date":"2019-02-14","arxiv_id":"1902.05509","repositories_listed":3,"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/multigrain-a-unified-image-embedding-for#ran","syntology_url":"https://syntology.ai/paper/1902.05509","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1902.05509"}},"official":{"repos":["facebookresearch/multigrain"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/video-trajectory-classification-and-anomaly","slug":"video-trajectory-classification-and-anomaly","title":"Video Trajectory Classification and Anomaly Detection Using Hybrid CNN-VAE","date":"2018-12-18","arxiv_id":"1812.07203","repositories_listed":3,"syntology":null},{"url":"/paper/fast-online-object-tracking-and-segmentation","slug":"fast-online-object-tracking-and-segmentation","title":"Fast Online Object Tracking and Segmentation: A Unifying Approach","date":"2018-12-12","arxiv_id":"1812.05050","repositories_listed":3,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"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) · 4 unverified","sample_list":"/paper/fast-online-object-tracking-and-segmentation#ran","syntology_url":"https://syntology.ai/paper/1812.05050","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.05050"}},"official":null}},{"url":"/paper/transferable-adversarial-attacks-for-image","slug":"transferable-adversarial-attacks-for-image","title":"Transferable Adversarial Attacks for Image and Video Object Detection","date":"2018-11-30","arxiv_id":"1811.12641","repositories_listed":3,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"4 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; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/transferable-adversarial-attacks-for-image#ran","syntology_url":"https://syntology.ai/paper/1811.12641","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.12641"}},"official":null}},{"url":"/paper/polarity-loss-for-zero-shot-object-detection","slug":"polarity-loss-for-zero-shot-object-detection","title":"Polarity Loss for Zero-shot Object Detection","date":"2018-11-22","arxiv_id":"1811.08982","repositories_listed":3,"syntology":null},{"url":"/paper/transferable-interactiveness-prior-for-human","slug":"transferable-interactiveness-prior-for-human","title":"Transferable Interactiveness Knowledge for Human-Object Interaction Detection","date":"2018-11-20","arxiv_id":"1811.08264","repositories_listed":3,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/transferable-interactiveness-prior-for-human#ran","syntology_url":"https://syntology.ai/paper/1811.08264","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.08264"}},"official":{"repos":["DirtyHarryLYL/Transferable-Interactiveness-Network"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/no-frills-human-object-interaction-detection","slug":"no-frills-human-object-interaction-detection","title":"No-Frills Human-Object Interaction Detection: Factorization, Layout Encodings, and Training Techniques","date":"2018-11-14","arxiv_id":"1811.05967","repositories_listed":3,"syntology":null},{"url":"/paper/training-frankensteins-creature-to-stack","slug":"training-frankensteins-creature-to-stack","title":"The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints","date":"2018-10-27","arxiv_id":"1810.11714","repositories_listed":3,"syntology":null},{"url":"/paper/semantic-aware-attention-based-deep-object-co","slug":"semantic-aware-attention-based-deep-object-co","title":"Semantic Aware Attention Based Deep Object Co-segmentation","date":"2018-10-16","arxiv_id":"1810.06859","repositories_listed":3,"syntology":null},{"url":"/paper/learning-regression-and-verification-networks","slug":"learning-regression-and-verification-networks","title":"Learning regression and verification networks for long-term visual tracking","date":"2018-09-12","arxiv_id":"1809.04320","repositories_listed":3,"syntology":null},{"url":"/paper/yolo3d-end-to-end-real-time-3d-oriented","slug":"yolo3d-end-to-end-real-time-3d-oriented","title":"YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud","date":"2018-08-07","arxiv_id":"1808.02350","repositories_listed":3,"syntology":null},{"url":"/paper/reverse-attention-for-salient-object","slug":"reverse-attention-for-salient-object","title":"Reverse Attention for Salient Object Detection","date":"2018-07-26","arxiv_id":"1807.09940","repositories_listed":3,"syntology":null},{"url":"/paper/where-are-the-blobs-counting-by-localization","slug":"where-are-the-blobs-counting-by-localization","title":"Where are the Blobs: Counting by Localization with Point Supervision","date":"2018-07-25","arxiv_id":"1807.09856","repositories_listed":3,"syntology":{"n":12,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":1,"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) · 4 unverified","sample_list":"/paper/where-are-the-blobs-counting-by-localization#ran","syntology_url":"https://syntology.ai/paper/1807.09856","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.09856"}},"official":null}},{"url":"/paper/big-little-net-an-efficient-multi-scale","slug":"big-little-net-an-efficient-multi-scale","title":"Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition","date":"2018-07-10","arxiv_id":"1807.03848","repositories_listed":3,"syntology":null},{"url":"/paper/localization-recall-precision-lrp-a-new","slug":"localization-recall-precision-lrp-a-new","title":"Localization Recall Precision (LRP): A New Performance Metric for Object Detection","date":"2018-07-04","arxiv_id":"1807.01696","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/localization-recall-precision-lrp-a-new#ran","syntology_url":"https://syntology.ai/paper/1807.01696","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.01696"}},"official":{"repos":["cancam/LRP"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/dense-object-nets-learning-dense-visual","slug":"dense-object-nets-learning-dense-visual","title":"Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation","date":"2018-06-22","arxiv_id":"1806.08756","repositories_listed":3,"syntology":null}],"record_sha256":"caef4a94a8adc8fc2e5988aadf0671778cd73ae52bef354637aa18ae858b269f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}