{"url":"/dataset/dexycb","name":"DexYCB","full_name":null,"description_markdown":"DexYCB is a dataset for capturing hand grasping of objects. It can be used three relevant tasks: 2D object and keypoint detection, 6D object pose estimation, and 3D hand pose estimation. \r\n\r\nThe dataset was built using 20 objects from the YCB-Video dataset, and consists of multiple trials from 10 subjects. For each trial, there is a target object with 2 to 4 other objects placed on a table. The subject is asked to start from a relaxed pose, pick up the target object, and hold it in the air. Some subjects were asked to pretend to hand over the object to someone across from them. Each action is recorded for 3 seconds, repeating the trial 5 times for each target object, each time with a random set of accompanied objects and placement. In total there are 100 trials per subject, and 1,000 trials in total for all subjects.\r\n\r\nSource: [DexYCB: A Benchmark for Capturing Hand Grasping of Objects](/paper/dexycb-a-benchmark-for-capturing-hand)","description_withheld":null,"homepage":"https://dex-ycb.github.io","introduced_date":"2021-04-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/dexycb-a-benchmark-for-capturing-hand","title":"DexYCB: A Benchmark for Capturing Hand Grasping of Objects","first_author":"Yu-Wei Chao","url":null},"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"3D Hand Pose Estimation","url":"/task/3d-hand-pose-estimation","datasets_with_task":"/datasets/task/3d-hand-pose-estimation"},{"name":"hand-object pose","url":"/task/hand-object-pose","datasets_with_task":"/datasets/task/hand-object-pose"}],"languages":[],"variants":["DexYCB"],"data_loaders":[],"num_papers_in_archive":94,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-hand-pose-estimation-on-dexycb","task":"3D Hand Pose Estimation","dataset_variant":"DexYCB","rows":11,"metrics":["Average MPJPE (mm)","Procrustes-Aligned MPJPE","MPVPE","VAUC","PA-MPVPE","PA-VAUC"],"first_row_in_archive_order":{"model":"HOISDF","paper":"/paper/hoisdf-constraining-3d-hand-object-pose","metrics":{"Average MPJPE (mm)":"10.1","MPVPE":"9.9","PA-MPVPE":"4.9","PA-VAUC":"90.2","Procrustes-Aligned MPJPE":"5.13","VAUC":"80.5"},"code_links":[{"title":"amathislab/hoisdf","url":"https://github.com/amathislab/hoisdf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/hand-object-pose-on-dexycb","task":"hand-object pose","dataset_variant":"DexYCB","rows":9,"metrics":["Average MPJPE (mm)","Procrustes-Aligned MPJPE","OCE","MCE","ADD-S"],"first_row_in_archive_order":{"model":"HOISDF","paper":"/paper/hoisdf-constraining-3d-hand-object-pose","metrics":{"ADD-S":"13.3","Average MPJPE (mm)":"10.1","MCE":"27.4","OCE":"18.4","Procrustes-Aligned MPJPE":"5.31"},"code_links":[{"title":"amathislab/hoisdf","url":"https://github.com/amathislab/hoisdf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mmhmr-generative-masked-modeling-for-hand","title":"MMHMR: Generative Masked Modeling for Hand Mesh Recovery","date":"2024-12-18","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/a-simple-baseline-for-efficient-hand-mesh","title":"A Simple Baseline for Efficient Hand Mesh Reconstruction","date":"2024-03-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":1,"samples_unverified":14,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/3d-hand-reconstruction-via-aggregating-intra","title":"3D Hand Reconstruction via Aggregating Intra and Inter Graphs Guided by Prior Knowledge for Hand-Object Interaction Scenario","date":"2024-03-04","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/hoisdf-constraining-3d-hand-object-pose","title":"HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields","date":"2024-02-26","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":23,"samples_ran":16,"samples_unverified":7,"pointer_only_for_licence":23,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/gsdf-geometry-driven-signed-distance","title":"gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction","date":"2023-04-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/harmonious-feature-learning-for-interactive","title":"Harmonious Feature Learning for Interactive Hand-Object Pose Estimation","date":"2023-01-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/h2onet-hand-occlusion-and-orientation-aware","title":"H2ONet: Hand-Occlusion-and-Orientation-Aware Network for Real-Time 3D Hand Mesh Reconstruction","date":"2023-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/interacting-hand-object-pose-estimation-via","title":"Interacting Hand-Object Pose Estimation via Dense Mutual Attention","date":"2022-11-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/alignsdf-pose-aligned-signed-distance-fields","title":"AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction","date":"2022-07-26","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/collaborative-learning-for-hand-and-object","title":"Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution","date":"2022-04-27","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/handoccnet-occlusion-robust-3d-hand-mesh","title":"HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network","date":"2022-03-28","rows_on_this_dataset":1,"code_links":0,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":6,"samples_unverified":2,"pointer_only_for_licence":8,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mobrecon-mobile-friendly-hand-mesh","title":"MobRecon: Mobile-Friendly Hand Mesh Reconstruction from Monocular Image","date":"2021-12-06","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":2,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/artiboost-boosting-articulated-3d-hand-object","title":"ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis","date":"2021-09-12","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/towards-unconstrained-joint-hand-object","title":"Towards unconstrained joint hand-object reconstruction from RGB videos","date":"2021-08-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/semi-supervised-3d-hand-object-poses","title":"Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time","date":"2021-06-09","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/end-to-end-human-pose-and-mesh-reconstruction","title":"End-to-End Human Pose and Mesh Reconstruction with Transformers","date":"2020-12-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/weakly-supervised-3d-hand-pose-estimation-via","title":"Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraints","date":"2020-03-20","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-joint-reconstruction-of-hands-and","title":"Learning joint reconstruction of hands and manipulated objects","date":"2019-04-11","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":61,"samples_ran":27,"samples_unverified":34,"pointer_only_for_licence":32,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}