{"url":"/sota/hand-object-pose-on-dexycb","task":{"name":"hand-object pose","url":"/task/hand-object-pose","note":null},"dataset":{"name":"DexYCB","url":"/dataset/dexycb"},"category":"Computer Vision","categories":["Computer Vision"],"category_note":null,"description":"6D pose estimation of hand and object","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":["Average MPJPE (mm)","Procrustes-Aligned MPJPE","OCE","MCE","ADD-S"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Average MPJPE (mm)":null,"Procrustes-Aligned MPJPE":null,"OCE":null,"MCE":null,"ADD-S":null}},"counts":{"rows":9,"rows_with_code":8,"rows_with_paper_page":9,"rows_dated":9,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"HOISDF","metrics":{"ADD-S":"13.3","Average MPJPE (mm)":"10.1","MCE":"27.4","OCE":"18.4","Procrustes-Aligned MPJPE":"5.31"},"uses_additional_data":false,"paper_date":"2024-02-26","paper":"/paper/hoisdf-constraining-3d-hand-object-pose","paper_url":"https://arxiv.org/abs/2402.17062v1","paper_title":"HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields","code":"https://github.com/amathislab/hoisdf","n_code_links":1,"syntology":{"n_ran":16,"n_unverified":7,"n_samples":23,"n_pointer_only_licence":23}},{"rank_in_archive_order":2,"model":"HFL-Net","metrics":{"ADD-S":"31.9","Average MPJPE (mm)":"11.9","MCE":"45.7","OCE":"39.8","Procrustes-Aligned MPJPE":"5.81"},"uses_additional_data":false,"paper_date":"2023-01-01","paper":"/paper/harmonious-feature-learning-for-interactive","paper_url":"http://openaccess.thecvf.com//content/CVPR2023/html/Lin_Harmonious_Feature_Learning_for_Interactive_Hand-Object_Pose_Estimation_CVPR_2023_paper.html","paper_title":"Harmonious Feature Learning for Interactive Hand-Object Pose Estimation","code":"https://github.com/lzfff12/hfl-net","n_code_links":1,"syntology":null},{"rank_in_archive_order":3,"model":"DMA","metrics":{"ADD-S":"15.9","Average MPJPE (mm)":"12.7","MCE":"32.6","OCE":"27.3","Procrustes-Aligned MPJPE":"6.86"},"uses_additional_data":false,"paper_date":"2022-11-16","paper":"/paper/interacting-hand-object-pose-estimation-via","paper_url":"https://arxiv.org/abs/2211.08805v1","paper_title":"Interacting Hand-Object Pose Estimation via Dense Mutual Attention","code":"https://github.com/rongakowang/densemutualattention","n_code_links":1,"syntology":{"n_ran":4,"n_unverified":1,"n_samples":5,"n_pointer_only_licence":0}},{"rank_in_archive_order":4,"model":"ArtiBoost","metrics":{"ADD-S":"-","Average MPJPE (mm)":"12.8","MCE":"-","OCE":"-","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2021-09-12","paper":"/paper/artiboost-boosting-articulated-3d-hand-object","paper_url":"https://arxiv.org/abs/2109.05488v2","paper_title":"ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis","code":"https://github.com/mvig-sjtu/artiboost","n_code_links":2,"syntology":null},{"rank_in_archive_order":5,"model":"gSDF","metrics":{"ADD-S":"-","Average MPJPE (mm)":"14.4","MCE":"-","OCE":"19.1","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2023-04-24","paper":"/paper/gsdf-geometry-driven-signed-distance","paper_url":"https://arxiv.org/abs/2304.11970v1","paper_title":"gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction","code":"https://github.com/zerchen/gSDF","n_code_links":1,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":1}},{"rank_in_archive_order":6,"model":"CLAGC","metrics":{"ADD-S":"-","Average MPJPE (mm)":"15.3","MCE":"-","OCE":"-","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2022-04-27","paper":"/paper/collaborative-learning-for-hand-and-object","paper_url":"https://arxiv.org/abs/2204.13062v1","paper_title":"Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":7,"model":"HMO","metrics":{"ADD-S":"-","Average MPJPE (mm)":"17.6","MCE":"-","OCE":"-","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2019-04-11","paper":"/paper/learning-joint-reconstruction-of-hands-and","paper_url":"http://arxiv.org/abs/1904.05767v1","paper_title":"Learning joint reconstruction of hands and manipulated objects","code":"https://github.com/hassony2/manopth","n_code_links":3,"syntology":null},{"rank_in_archive_order":8,"model":"UHO","metrics":{"ADD-S":"-","Average MPJPE (mm)":"18.8","MCE":"52.5","OCE":"-","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2021-08-16","paper":"/paper/towards-unconstrained-joint-hand-object","paper_url":"https://arxiv.org/abs/2108.07044v2","paper_title":"Towards unconstrained joint hand-object reconstruction from RGB videos","code":"https://github.com/hassony2/homan","n_code_links":1,"syntology":null},{"rank_in_archive_order":9,"model":"AlignSDF","metrics":{"ADD-S":"-","Average MPJPE (mm)":"19.0","MCE":"-","OCE":"19.1","Procrustes-Aligned MPJPE":"-"},"uses_additional_data":false,"paper_date":"2022-07-26","paper":"/paper/alignsdf-pose-aligned-signed-distance-fields","paper_url":"https://arxiv.org/abs/2207.12909v1","paper_title":"AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction","code":"https://github.com/zerchen/AlignSDF","n_code_links":2,"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 7,081 of the 9,623 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":9623,"papers_checked":7081,"papers_extracted_not_yet_verified":217,"boards_without_verdict":27,"papers_not_yet_extracted":2325},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-25T09:33:49+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":3,"rows_with_any_sample_ran":3,"distinct_papers_with_graph_line":3,"distinct_papers_with_any_sample_ran":3,"samples_over_distinct_papers":{"n_ran":21,"n_unverified":8,"n_samples":29,"n_pointer_only_licence":24,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":21,"n_unverified":8,"n_samples":29,"n_pointer_only_licence":24,"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"}}}