{"url":"/dataset/mupots-3d","name":"MuPoTS-3D","full_name":"Multiperson Pose Test Set in 3DMulti-person Pose estimation Test Set in 3D","description_markdown":"MuPoTs-3D (Multi-person Pose estimation Test Set in 3D) is a dataset for pose estimation composed of more than 8,000 frames from 20 real-world scenes with up to three subjects. The poses are annotated with a 14-point skeleton model.\r\n\r\nSource: [DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild](https://arxiv.org/abs/2008.09457)\r\nImage Source: [http://gvv.mpi-inf.mpg.de/projects/SingleShotMultiPerson/](http://gvv.mpi-inf.mpg.de/projects/SingleShotMultiPerson/)","description_withheld":null,"homepage":"http://gvv.mpi-inf.mpg.de/projects/SingleShotMultiPerson/","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/single-shot-multi-person-3d-pose-estimation","title":"Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB","first_author":"Dushyant Mehta","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"3D Multi-Person Pose Estimation","url":"/task/3d-multi-person-pose-estimation","datasets_with_task":"/datasets/task/3d-multi-person-pose-estimation"},{"name":"3D Multi-Person Pose Estimation (root-relative)","url":"/task/3d-multi-person-pose-estimation-root-relative","datasets_with_task":"/datasets/task/3d-multi-person-pose-estimation-root-relative"},{"name":"3D Multi-Person Pose Estimation (absolute)","url":"/task/3d-multi-person-pose-estimation-absolute","datasets_with_task":"/datasets/task/3d-multi-person-pose-estimation-absolute"},{"name":"Unsupervised 3D Multi-Person Pose Estimation","url":"/task/unsupervised-3d-multi-person-pose-estimation","datasets_with_task":"/datasets/task/unsupervised-3d-multi-person-pose-estimation"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["MuPoTS-3D"],"data_loaders":[],"num_papers_in_archive":70,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-multi-person-pose-estimation-root-relative","task":"3D Multi-Person Pose Estimation (root-relative)","dataset_variant":"MuPoTS-3D","rows":20,"metrics":["3DPCK","MPJPE","AUC"],"first_row_in_archive_order":{"model":"TDBU_Net","paper":"/paper/monocular-3d-multi-person-pose-estimation-by","metrics":{"3DPCK":"89.6"},"code_links":[{"title":"3dpose/3D-Multi-Person-Pose","url":"https://github.com/3dpose/3D-Multi-Person-Pose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-multi-person-pose-estimation-absolute-on","task":"3D Multi-Person Pose Estimation (absolute)","dataset_variant":"MuPoTS-3D","rows":14,"metrics":["3DPCK","MPJPE"],"first_row_in_archive_order":{"model":"POTR-3D","paper":"/paper/towards-robust-and-smooth-3d-multi-person","metrics":{"3DPCK":"50.9"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-multi-person-human-pose-estimation-on","task":"3D Multi-Person Pose Estimation","dataset_variant":"MuPoTS-3D","rows":10,"metrics":["3DPCK"],"first_row_in_archive_order":{"model":"Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement","paper":"/paper/multi-person-3d-pose-and-shape-estimation-via","metrics":{"3DPCK":"89.9"},"code_links":[{"title":"JunukCha/MultiPerson","url":"https://github.com/JunukCha/MultiPerson"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/multi-hmr-multi-person-whole-body-human-mesh","title":"Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot","date":"2024-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":8,"samples_unverified":1,"pointer_only_for_licence":9,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/towards-robust-and-smooth-3d-multi-person","title":"Towards Robust and Smooth 3D Multi-Person Pose Estimation from Monocular Videos in the Wild","date":"2023-09-15","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/three-recipes-for-better-3d-pseudo-gts-of-3d","title":"Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild","date":"2023-04-10","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multi-person-3d-pose-and-shape-estimation-via","title":"Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement","date":"2022-10-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/explicit-occlusion-reasoning-for-multi-person","title":"Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation","date":"2022-07-29","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/dynamic-graph-reasoning-for-multi-person-3d","title":"Dynamic Graph Reasoning for Multi-person 3D Pose Estimation","date":"2022-07-22","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/virtualpose-learning-generalizable-3d-human","title":"VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Data","date":"2022-07-20","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/mug-multi-human-graph-network-for-3d-mesh","title":"MUG: Multi-human Graph Network for 3D Mesh Reconstruction from 2D Pose","date":"2022-05-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/dual-networks-based-3d-multi-person-pose","title":"Dual networks based 3D Multi-Person Pose Estimation from Monocular Video","date":"2022-05-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/permutation-invariant-relational-network-for","title":"Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation","date":"2022-04-11","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/distribution-aware-single-stage-models-for","title":"Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation","date":"2022-03-15","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":1,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/body-meshes-as-points","title":"Body Meshes as Points","date":"2021-05-06","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":1,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/3dcrowdnet-2d-human-pose-guided3d-crowd-human","title":"Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes","date":"2021-04-15","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":3,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deep-monocular-3d-human-pose-estimation-via","title":"Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting","date":"2021-04-08","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/monocular-3d-multi-person-pose-estimation-by","title":"Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks","date":"2021-04-05","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/graph-and-temporal-convolutional-networks-for","title":"Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos","date":"2020-12-22","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/temporal-smoothing-for-3d-human-pose","title":"Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded People","date":"2020-10-31","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/pi-net-pose-interacting-network-for-multi","title":"PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation","date":"2020-10-11","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/smap-single-shot-multi-person-absolute-3d","title":"SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation","date":"2020-08-26","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/unsupervised-cross-modal-alignment-for-multi","title":"Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation","date":"2020-08-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/hmor-hierarchical-multi-person-ordinal","title":"HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation","date":"2020-08-01","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/hdnet-human-depth-estimation-for-multi-person","title":"HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization","date":"2020-07-17","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/multi-person-absolute-3d-human-pose","title":"Multi-Person Absolute 3D Human Pose Estimation with Weak Depth Supervision","date":"2020-04-08","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/multi-person-3d-human-pose-estimation-from","title":"Multi-Person 3D Human Pose Estimation from Monocular Images","date":"2019-09-24","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/camera-distance-aware-top-down-approach-for","title":"Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image","date":"2019-07-26","rows_on_this_dataset":2,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":1,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/xnect-real-time-multi-person-3d-human-pose","title":"XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera","date":"2019-07-01","rows_on_this_dataset":1,"code_links":4,"syntology":null},{"paper":"/paper/absolute-human-pose-estimation-with-depth","title":"Absolute Human Pose Estimation with Depth Prediction Network","date":"2019-04-11","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/single-shot-multi-person-3d-pose-estimation","title":"Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB","date":"2017-12-09","rows_on_this_dataset":2,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/lcr-net-localization-classification","title":"LCR-Net: Localization-Classification-Regression for Human Pose","date":"2017-07-01","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":8,"samples_harvested":41,"samples_ran":19,"samples_unverified":22,"pointer_only_for_licence":11,"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."}