{"url":"/sota/3d-multi-person-pose-estimation-on-shelf","task":{"name":"3D Multi-Person Pose Estimation","url":"/task/3d-multi-person-pose-estimation","note":null},"dataset":{"name":"Shelf","url":"/dataset/campus-shelf"},"category":"Computer Vision","categories":["Computer Vision"],"category_note":null,"description":"This task aims to solve root-relative 3D multi-person pose estimation. No human bounding box and root joint coordinate groundtruth are used in testing time.\r\n\r\n<span style=\"color:grey; opacity: 0.6\">( Image credit: [RootNet](https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE) )</span>","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["PCP3D","MPJPE"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"PCP3D":null,"MPJPE":null}},"counts":{"rows":27,"rows_with_code":13,"rows_with_paper_page":27,"rows_dated":26,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"RapidPoseTriangulation (with corrected labels)","metrics":{"MPJPE":"47.5","PCP3D":"100"},"uses_additional_data":false,"paper_date":"2025-03-27","paper":"/paper/rapidposetriangulation-multi-view-multi","paper_url":"https://arxiv.org/abs/2503.21692v1","paper_title":"RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in a Millisecond","code":"https://gitlab.com/Percipiote/RapidPoseTriangulation","n_code_links":1,"syntology":null},{"rank_in_archive_order":2,"model":"Feiz et al. (Kinematics)","metrics":{"PCP3D":"98.6"},"uses_additional_data":false,"paper_date":"2025-04-11","paper":"/paper/multi-person-physics-based-pose-estimation","paper_url":"https://arxiv.org/abs/2504.08175v1","paper_title":"Multi-person Physics-based Pose Estimation for Combat Sports","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":3,"model":"QuickPose","metrics":{"PCP3D":"98.1"},"uses_additional_data":false,"paper_date":"2022-07-22","paper":"/paper/quickpose-real-time-multi-view-multi-person","paper_url":"https://dl.acm.org/doi/abs/10.1145/3528233.3530746","paper_title":"QuickPose: Real-time Multi-view Multi-person Pose Estimation in Crowded Scenes","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":4,"model":"Zhang et al.","metrics":{"PCP3D":"98.1"},"uses_additional_data":false,"paper_date":"2021-08-23","paper":"/paper/lightweight-multi-person-total-motion-capture","paper_url":"https://arxiv.org/abs/2108.10378v1","paper_title":"Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":5,"model":"PlaneSweepPose","metrics":{"PCP3D":"97.9"},"uses_additional_data":false,"paper_date":"2021-04-06","paper":"/paper/multi-view-multi-person-3d-pose-estimation","paper_url":"https://arxiv.org/abs/2104.02273v1","paper_title":"Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo","code":"https://github.com/jiahaoLjh/PlaneSweepPose","n_code_links":1,"syntology":{"n_ran":6,"n_unverified":3,"n_samples":9,"n_pointer_only_licence":0}},{"rank_in_archive_order":6,"model":"TesseTrack (correct)","metrics":{"PCP3D":"97.9"},"uses_additional_data":false,"paper_date":"2021-06-16","paper":"/paper/tessetrack-end-to-end-learnable-multi-person","paper_url":"http://www.cs.cmu.edu/~ILIM/projects/IM/TesseTrack/","paper_title":"TesseTrack: End-to-End Learnable Multi-Person Articulated 3D Pose Tracking","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":7,"model":"PRGN","metrics":{"PCP3D":"97.7"},"uses_additional_data":false,"paper_date":"2021-09-13","paper":"/paper/graph-based-3d-multi-person-pose-estimation","paper_url":"https://arxiv.org/abs/2109.05885v1","paper_title":"Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images","code":"https://github.com/wusize/multiview_pose","n_code_links":1,"syntology":{"n_ran":19,"n_unverified":3,"n_samples":22,"n_pointer_only_licence":0}},{"rank_in_archive_order":8,"model":"UTTM","metrics":{"PCP3D":"97.7"},"uses_additional_data":false,"paper_date":"2023-02-08","paper":"/paper/a-unified-multi-view-multi-person-tracking","paper_url":"https://arxiv.org/abs/2302.03820v1","paper_title":"A Unified Multi-view Multi-person Tracking Framework","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":9,"model":"4D Association Pose","metrics":{"PCP3D":"97.6"},"uses_additional_data":false,"paper_date":"2020-02-28","paper":"/paper/4d-association-graph-for-realtime-multi","paper_url":"https://arxiv.org/abs/2002.12625v1","paper_title":"4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras","code":"https://github.com/zhangyux15/4d_association","n_code_links":1,"syntology":null},{"rank_in_archive_order":10,"model":"Faster VoxelPose","metrics":{"PCP3D":"97.6"},"uses_additional_data":false,"paper_date":"2022-07-22","paper":"/paper/faster-voxelpose-real-time-3d-human-pose","paper_url":"https://arxiv.org/abs/2207.10955v1","paper_title":"Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection","code":"https://github.com/AlvinYH/Faster-VoxelPose","n_code_links":1,"syntology":{"n_ran":0,"n_unverified":4,"n_samples":4,"n_pointer_only_licence":4}},{"rank_in_archive_order":11,"model":"SmartEdgeSensor","metrics":{"PCP3D":"97.4"},"uses_additional_data":false,"paper_date":"2021-06-28","paper":"/paper/real-time-multi-view-3d-human-pose-estimation","paper_url":"https://arxiv.org/abs/2106.14729v1","paper_title":"Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge Sensors","code":"https://github.com/AIS-Bonn/SmartEdgeSensor3DHumanPose","n_code_links":1,"syntology":null},{"rank_in_archive_order":12,"model":"MvP","metrics":{"PCP3D":"97.4"},"uses_additional_data":false,"paper_date":"2021-11-07","paper":"/paper/direct-multi-view-multi-person-3d-pose","paper_url":"https://arxiv.org/abs/2111.04076v2","paper_title":"Direct Multi-view Multi-person 3D Pose Estimation","code":"https://github.com/openxrlab/xrmocap","n_code_links":2,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":13,"model":"Huang et al.","metrics":{"PCP3D":"97.4"},"uses_additional_data":false,"paper_date":null,"paper":"/paper/end-to-end-dynamic-matching-network-for-multi","paper_url":"https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6258_ECCV_2020_paper.php","paper_title":"End-to-end Dynamic Matching Network for Multi-view Multi-person 3d Pose Estimation","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":14,"model":"Part-aware Pose","metrics":{"PCP3D":"97.39"},"uses_additional_data":false,"paper_date":"2021-06-22","paper":"/paper/part-aware-measurement-for-robust-multi-view-1","paper_url":"https://arxiv.org/abs/2106.11589v1","paper_title":"Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking","code":"https://github.com/ivclab/Part-Aware_Measurement_for_3D_Pose_Estimation_and_Tracking","n_code_links":1,"syntology":null},{"rank_in_archive_order":15,"model":"VTP","metrics":{"MPJPE":"56.3","PCP3D":"97.3"},"uses_additional_data":false,"paper_date":"2022-05-25","paper":"/paper/vtp-volumetric-transformer-for-multi-view","paper_url":"https://arxiv.org/abs/2205.12602v1","paper_title":"VTP: Volumetric Transformer for Multi-view Multi-person 3D Pose Estimation","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":16,"model":"VoxelTrack","metrics":{"PCP3D":"97.1"},"uses_additional_data":false,"paper_date":"2021-08-05","paper":"/paper/voxeltrack-multi-person-3d-human-pose","paper_url":"https://arxiv.org/abs/2108.02452v1","paper_title":"VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":17,"model":"VoxelPose","metrics":{"PCP3D":"97"},"uses_additional_data":false,"paper_date":"2020-04-13","paper":"/paper/end-to-end-estimation-of-multi-person-3d","paper_url":"https://arxiv.org/abs/2004.06239v4","paper_title":"VoxelPose: Towards Multi-Camera 3D Human Pose Estimation in Wild Environment","code":"https://github.com/open-mmlab/mmpose","n_code_links":2,"syntology":null},{"rank_in_archive_order":18,"model":"MVPose","metrics":{"PCP3D":"96.9"},"uses_additional_data":false,"paper_date":"2019-01-14","paper":"/paper/fast-and-robust-multi-person-3d-pose","paper_url":"http://arxiv.org/abs/1901.04111v1","paper_title":"Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views","code":"https://github.com/zju3dv/EasyMocap","n_code_links":4,"syntology":{"n_ran":2,"n_unverified":17,"n_samples":19,"n_pointer_only_licence":0}},{"rank_in_archive_order":19,"model":"Multi Person Pose","metrics":{"PCP3D":"96.9"},"uses_additional_data":false,"paper_date":"2021-10-05","paper":"/paper/shape-aware-multi-person-pose-estimation-from-1","paper_url":"https://arxiv.org/abs/2110.02330v1","paper_title":"Shape-aware Multi-Person Pose Estimation from Multi-View Images","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":20,"model":"crossview_3d_pose_tracking","metrics":{"PCP3D":"96.8"},"uses_additional_data":false,"paper_date":"2020-03-09","paper":"/paper/cross-view-tracking-for-multi-human-3d-pose","paper_url":"https://arxiv.org/abs/2003.03972v3","paper_title":"Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS","code":"https://github.com/longcw/crossview_3d_pose_tracking","n_code_links":2,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":1}},{"rank_in_archive_order":21,"model":"Cross-View","metrics":{"PCP3D":"96.8"},"uses_additional_data":false,"paper_date":"2020-03-09","paper":"/paper/cross-view-tracking-for-multi-human-3d-pose","paper_url":"https://arxiv.org/abs/2003.03972v3","paper_title":"Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS","code":"https://github.com/longcw/crossview_3d_pose_tracking","n_code_links":2,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":1}},{"rank_in_archive_order":22,"model":"Tanke and Gall","metrics":{"PCP3D":"96.0"},"uses_additional_data":false,"paper_date":"2021-01-24","paper":"/paper/iterative-greedy-matching-for-3d-human-pose","paper_url":"https://arxiv.org/abs/2101.09745v1","paper_title":"Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views","code":"https://github.com/jutanke/mv3dpose","n_code_links":1,"syntology":null},{"rank_in_archive_order":23,"model":"Light3DPose","metrics":{"PCP3D":"89.8"},"uses_additional_data":false,"paper_date":"2020-04-06","paper":"/paper/light3dpose-real-time-multi-person-3d","paper_url":"https://arxiv.org/abs/2004.02688v1","paper_title":"Light3DPose: Real-time Multi-Person 3D PoseEstimation from Multiple Views","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":24,"model":"Ershadi-Nasab model","metrics":{"PCP3D":"88"},"uses_additional_data":false,"paper_date":"2017-09-04","paper":"/paper/multiple-human-3d-pose-estimation-from","paper_url":"https://link.springer.com/article/10.1007/s11042-017-5133-8","paper_title":"Multiple human 3d pose estimation from multiview images","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":25,"model":"Belagiannis model v.3","metrics":{"PCP3D":"77.5"},"uses_additional_data":false,"paper_date":"2016-10-01","paper":"/paper/3d-pictorial-structures-revisited-multiple","paper_url":"https://ieeexplore.ieee.org/document/7360209/authors#authors","paper_title":"3D Pictorial Structures Revisited: Multiple Human Pose Estimation","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":26,"model":"Belagiannis model v.2","metrics":{"PCP3D":"76"},"uses_additional_data":false,"paper_date":"2014-09-06","paper":"/paper/multiple-human-pose-estimation-with","paper_url":"http://campar.in.tum.de/pub/belagiannis2014eccvChalearn/belagiannis2014eccvChalearn.pdf","paper_title":"Multiple human pose estimation with temporally consistent 3d pictorial structures","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":27,"model":"Belagiannis model v.1","metrics":{"PCP3D":"71.4"},"uses_additional_data":false,"paper_date":"2014-06-01","paper":"/paper/3d-pictorial-structures-for-multiple-human","paper_url":"http://openaccess.thecvf.com/content_cvpr_2014/html/Belagiannis_3D_Pictorial_Structures_2014_CVPR_paper.html","paper_title":"3D Pictorial Structures for Multiple Human Pose Estimation","code":null,"n_code_links":0,"syntology":null}],"since_archive":{"claim":"Results that newer papers report for their own method, placed here by Syntology. A model pointed at the cell in the paper's own table; the number was read from that cell and checked against this leaderboard's metric, dataset, split and scale; an independent check that saw this leaderboard's other rows and every other leaderboard on the same dataset accepted it. Not reviewed by the paper's authors or by the archive's editors, and not ranked against the archive rows.","extraction_file_present":true,"measurement":{"test_papers":883,"papers_with_output":881,"judged_true":108,"judged":110,"wilson95_lower":0.9361,"measured_on":"2026-09-24","frozen_commit":"0e3de0df94"},"measurement_note":"blind adjudication of accepted entries on a held-out split of archive papers, rules frozen before the test","coverage":{"sentence":"Syntology has checked 6,264 of the 9,581 papers on this site that are newer than the archive; results from the others appear after they are checked.","complete":false,"papers_newer_than_archive":9581,"papers_checked":6264,"papers_extracted_not_yet_verified":0,"boards_without_verdict":2,"papers_not_yet_extracted":3316},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":7,"rows_with_any_sample_ran":6,"distinct_papers_with_graph_line":6,"distinct_papers_with_any_sample_ran":5,"samples_over_distinct_papers":{"n_ran":29,"n_unverified":27,"n_samples":56,"n_pointer_only_licence":5,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":30,"n_unverified":27,"n_samples":57,"n_pointer_only_licence":6,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}