{"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":"/dataset/waymo-open-dataset/papers/ran/1","list_of":"/dataset/waymo-open-dataset","dataset":"Waymo Open Dataset","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","key_notes":{"samples_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'","samples_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)"},"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 dataset or check it against this dataset'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.","population":"every paper with a leaderboard row on this dataset's benchmarks (the benchmark-backed subset): the archive's own papers-using-this-dataset list was never published, so this is not that list; num_papers_in_archive is the archive's own count","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,13],"of":13,"counts":{"papers_with_a_benchmark_row":34,"with_a_code_link":34,"where_syntology_ran_a_sample":13,"not_listed_spam_title":0,"listed":34,"listed_where_code_ran":13,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":13,"every_run_a_failure_of_syntologys_instrument":0,"listed_with_a_run_with_no_instrument_failure":13,"listed_every_run_a_failure_of_syntologys_instrument":0,"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 with at least one leaderboard row on this dataset's benchmarks; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/dataset/waymo-open-dataset/papers/ran/1","prev":null,"next":null,"papers":[{"paper":"/paper/scene-centric-unsupervised-panoptic","slug":"scene-centric-unsupervised-panoptic","title":"Scene-Centric Unsupervised Panoptic Segmentation","date":"2025-04-02","arxiv_id":"2504.01955","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":8,"samples_ran":3,"samples_constructed":0,"samples_ran_checked":3,"samples_ran_instrument_failed":0,"samples_unverified":5,"pointer_only_for_licence":0,"official":{"repos":["visinf/cups"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/scene-centric-unsupervised-panoptic#ran","syntology_url":"https://syntology.ai/paper/2504.01955","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2504.01955"}}}},{"paper":"/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","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":7,"samples_ran":6,"samples_constructed":0,"samples_ran_checked":6,"samples_ran_instrument_failed":0,"samples_unverified":1,"pointer_only_for_licence":0,"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"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","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"}}}},{"paper":"/paper/unsupervised-universal-image-segmentation","slug":"unsupervised-universal-image-segmentation","title":"Unsupervised Universal Image Segmentation","date":"2023-12-28","arxiv_id":"2312.17243","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":15,"samples_ran":13,"samples_constructed":0,"samples_ran_checked":6,"samples_ran_instrument_failed":7,"samples_unverified":2,"pointer_only_for_licence":1,"official":{"repos":["u2seg/u2seg"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["listed","official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/unsupervised-universal-image-segmentation#ran","syntology_url":"https://syntology.ai/paper/2312.17243","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.17243"}}}},{"paper":"/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","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":8,"samples_ran":7,"samples_constructed":0,"samples_ran_checked":7,"samples_ran_instrument_failed":0,"samples_unverified":1,"pointer_only_for_licence":1,"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"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","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"}}}},{"paper":"/paper/centerformer-center-based-transformer-for-3d","slug":"centerformer-center-based-transformer-for-3d","title":"CenterFormer: Center-based Transformer for 3D Object Detection","date":"2022-09-12","arxiv_id":"2209.05588","rows_on_this_dataset":4,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":6,"samples_ran":5,"samples_constructed":0,"samples_ran_checked":5,"samples_ran_instrument_failed":0,"samples_unverified":1,"pointer_only_for_licence":0,"official":{"repos":["tusimple/centerformer"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/centerformer-center-based-transformer-for-3d#ran","syntology_url":"https://syntology.ai/paper/2209.05588","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.05588"}}}},{"paper":"/paper/deviant-depth-equivariant-network-for","slug":"deviant-depth-equivariant-network-for","title":"DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection","date":"2022-07-21","arxiv_id":"2207.10758","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":15,"samples_ran":9,"samples_constructed":3,"samples_ran_checked":7,"samples_ran_instrument_failed":2,"samples_unverified":6,"pointer_only_for_licence":0,"official":{"repos":["abhi1kumar/deviant"],"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":["listed","official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/deviant-depth-equivariant-network-for#ran","syntology_url":"https://syntology.ai/paper/2207.10758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.10758"}}}},{"paper":"/paper/pyramid-r-cnn-towards-better-performance-and","slug":"pyramid-r-cnn-towards-better-performance-and","title":"Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection","date":"2021-09-06","arxiv_id":"2109.02499","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":4,"samples_ran":1,"samples_constructed":1,"samples_ran_checked":1,"samples_ran_instrument_failed":0,"samples_unverified":3,"pointer_only_for_licence":4,"official":null,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/pyramid-r-cnn-towards-better-performance-and#ran","syntology_url":"https://syntology.ai/paper/2109.02499","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.02499"}}}},{"paper":"/paper/geometry-uncertainty-projection-network-for","slug":"geometry-uncertainty-projection-network-for","title":"Geometry Uncertainty Projection Network for Monocular 3D Object Detection","date":"2021-07-29","arxiv_id":"2107.13774","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":21,"samples_ran":16,"samples_constructed":0,"samples_ran_checked":10,"samples_ran_instrument_failed":6,"samples_unverified":5,"pointer_only_for_licence":2,"official":{"repos":["supermhp/gupnet"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/geometry-uncertainty-projection-network-for#ran","syntology_url":"https://syntology.ai/paper/2107.13774","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.13774"}}}},{"paper":"/paper/m3detr-multi-representation-multi-scale","slug":"m3detr-multi-representation-multi-scale","title":"M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers","date":"2021-04-24","arxiv_id":"2104.11896","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":7,"samples_ran":4,"samples_constructed":0,"samples_ran_checked":4,"samples_ran_instrument_failed":0,"samples_unverified":3,"pointer_only_for_licence":0,"official":{"repos":["rayguan97/M3DeTR"],"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"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/m3detr-multi-representation-multi-scale#ran","syntology_url":"https://syntology.ai/paper/2104.11896","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.11896"}}}},{"paper":"/paper/center-based-3d-object-detection-and-tracking","slug":"center-based-3d-object-detection-and-tracking","title":"Center-based 3D Object Detection and Tracking","date":"2020-06-19","arxiv_id":"2006.11275","rows_on_this_dataset":4,"code_links":13,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":22,"samples_ran":19,"samples_constructed":0,"samples_ran_checked":16,"samples_ran_instrument_failed":3,"samples_unverified":3,"pointer_only_for_licence":4,"official":{"repos":["tianweiy/CenterPoint"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/center-based-3d-object-detection-and-tracking#ran","syntology_url":"https://syntology.ai/paper/2006.11275","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.11275"}}}},{"paper":"/paper/pv-rcnn-point-voxel-feature-set-abstraction","slug":"pv-rcnn-point-voxel-feature-set-abstraction","title":"PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection","date":"2019-12-31","arxiv_id":"1912.13192","rows_on_this_dataset":4,"code_links":12,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":16,"samples_ran":13,"samples_constructed":0,"samples_ran_checked":13,"samples_ran_instrument_failed":0,"samples_unverified":3,"pointer_only_for_licence":3,"official":{"repos":["open-mmlab/OpenPCDet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/pv-rcnn-point-voxel-feature-set-abstraction#ran","syntology_url":"https://syntology.ai/paper/1912.13192","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.13192"}}}},{"paper":"/paper/m3d-rpn-monocular-3d-region-proposal-network","slug":"m3d-rpn-monocular-3d-region-proposal-network","title":"M3D-RPN: Monocular 3D Region Proposal Network for Object Detection","date":"2019-07-13","arxiv_id":"1907.06038","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":21,"samples_ran":9,"samples_constructed":0,"samples_ran_checked":8,"samples_ran_instrument_failed":1,"samples_unverified":12,"pointer_only_for_licence":1,"official":{"repos":["garrickbrazil/M3D-RPN"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":10,"ran_from_kinds":["listed","official"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/m3d-rpn-monocular-3d-region-proposal-network#ran","syntology_url":"https://syntology.ai/paper/1907.06038","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.06038"}}}},{"paper":"/paper/simple-online-and-realtime-tracking-with-a","slug":"simple-online-and-realtime-tracking-with-a","title":"Simple Online and Realtime Tracking with a Deep Association Metric","date":"2017-03-21","arxiv_id":"1703.07402","rows_on_this_dataset":1,"code_links":75,"syntology":{"read_at":"2026-09-28T10:30:06+00:00","samples_harvested":40,"samples_ran":29,"samples_constructed":0,"samples_ran_checked":24,"samples_ran_instrument_failed":5,"samples_unverified":11,"pointer_only_for_licence":9,"official":{"repos":["nwojke/deep_sort"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]},"claim":"Per-sample execution on synthesized fixtures; not a correctness claim.","sample_list":"/paper/simple-online-and-realtime-tracking-with-a#ran","syntology_url":"https://syntology.ai/paper/1703.07402","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1703.07402"}}}}],"record_sha256":"04aa5a79e6107062257fd1b33f1263e7e25a0a28f6f07beb66eacf236aa6f22d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}