{"url":"/dataset/mpii","name":"MPII","full_name":"MPII Human Pose","description_markdown":"The **MPII** Human Pose Dataset for single person pose estimation is composed of about 25K images of which 15K are training samples, 3K are validation samples and 7K are testing samples (which labels are withheld by the authors). The images are taken from YouTube videos covering 410 different human activities and the poses are manually annotated with up to 16 body joints.\r\n\r\nSource: [2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning](https://arxiv.org/abs/1802.09232)\r\nImage Source: [http://human-pose.mpi-inf.mpg.de/](http://human-pose.mpi-inf.mpg.de/)","description_withheld":null,"homepage":"http://human-pose.mpi-inf.mpg.de/","introduced_date":"2014-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/2d-human-pose-estimation-new-benchmark-and","title":"2D Human Pose Estimation: New Benchmark and State of the Art Analysis","first_author":"Mykhaylo Andriluka","url":null},"license":{"name":"Simplified BSD","url":"http://human-pose.mpi-inf.mpg.de/bsd.txt"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"Temporal Action Localization","url":"/task/action-recognition","datasets_with_task":"/datasets/task/action-recognition"},{"name":"Multi-Person Pose Estimation","url":"/task/multi-person-pose-estimation","datasets_with_task":"/datasets/task/multi-person-pose-estimation"},{"name":"Keypoint Detection","url":"/task/keypoint-detection","datasets_with_task":"/datasets/task/keypoint-detection"}],"languages":[{"name":"Turkish","url":"/datasets/language/turkish"}],"variants":["MPII","MPII Multi-Person","MPII Single Person"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/2d_body_keypoint.md#mpii","frameworks":["pytorch"]}],"num_papers_in_archive":495,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/keypoint-detection-on-mpii-multi-person","task":"Keypoint Detection","dataset_variant":"MPII Multi-Person","rows":9,"metrics":["mAP@0.5"],"first_row_in_archive_order":{"model":"AlphaPose","paper":"/paper/rmpe-regional-multi-person-pose-estimation","metrics":{"mAP@0.5":"82.1%"},"code_links":[{"title":"MVIG-SJTU/AlphaPose","url":"https://github.com/MVIG-SJTU/AlphaPose"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"mindspore-ai/models","url":"https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose"},{"title":"MVIG-SJTU/RMPE","url":"https://github.com/MVIG-SJTU/RMPE"},{"title":"ManifoldFR/recvis-project","url":"https://github.com/ManifoldFR/recvis-project"},{"title":"Fangyh09/pose_nms","url":"https://github.com/Fangyh09/pose_nms"},{"title":"MattyChoi/PoseMachines","url":"https://github.com/MattyChoi/PoseMachines"},{"title":"2023-MindSpore-4/Code8","url":"https://github.com/2023-MindSpore-4/Code8/tree/main/AlphaPose"},{"title":"yangyucheng000/AlphaPose","url":"https://github.com/yangyucheng000/AlphaPose"},{"title":"MindSpore-paper-code-3/code1","url":"https://github.com/MindSpore-paper-code-3/code1/tree/main/AlphaPose"},{"title":"2023-MindSpore-1/ms-code-199","url":"https://github.com/2023-MindSpore-1/ms-code-199"},{"title":"2023-MindSpore-1/ms-code-22","url":"https://github.com/2023-MindSpore-1/ms-code-22"},{"title":"lyqcom/alphapose","url":"https://github.com/lyqcom/alphapose"},{"title":"yuanyuanfyy/yycode","url":"https://github.com/yuanyuanfyy/yycode/tree/mindsporecode/AlphaPose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-person-pose-estimation-on-mpii-multi","task":"Multi-Person Pose Estimation","dataset_variant":"MPII Multi-Person","rows":9,"metrics":["AP"],"first_row_in_archive_order":{"model":"AlphaPose","paper":"/paper/rmpe-regional-multi-person-pose-estimation","metrics":{"AP":"82.1%"},"code_links":[{"title":"MVIG-SJTU/AlphaPose","url":"https://github.com/MVIG-SJTU/AlphaPose"},{"title":"osmr/imgclsmob","url":"https://github.com/osmr/imgclsmob"},{"title":"mindspore-ai/models","url":"https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose"},{"title":"MVIG-SJTU/RMPE","url":"https://github.com/MVIG-SJTU/RMPE"},{"title":"ManifoldFR/recvis-project","url":"https://github.com/ManifoldFR/recvis-project"},{"title":"Fangyh09/pose_nms","url":"https://github.com/Fangyh09/pose_nms"},{"title":"MattyChoi/PoseMachines","url":"https://github.com/MattyChoi/PoseMachines"},{"title":"2023-MindSpore-4/Code8","url":"https://github.com/2023-MindSpore-4/Code8/tree/main/AlphaPose"},{"title":"yangyucheng000/AlphaPose","url":"https://github.com/yangyucheng000/AlphaPose"},{"title":"MindSpore-paper-code-3/code1","url":"https://github.com/MindSpore-paper-code-3/code1/tree/main/AlphaPose"},{"title":"2023-MindSpore-1/ms-code-199","url":"https://github.com/2023-MindSpore-1/ms-code-199"},{"title":"2023-MindSpore-1/ms-code-22","url":"https://github.com/2023-MindSpore-1/ms-code-22"},{"title":"lyqcom/alphapose","url":"https://github.com/lyqcom/alphapose"},{"title":"yuanyuanfyy/yycode","url":"https://github.com/yuanyuanfyy/yycode/tree/mindsporecode/AlphaPose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/pose-estimation-on-mpii-single-person","task":"Pose Estimation","dataset_variant":"MPII Single Person","rows":5,"metrics":["PCKh@0.5","PCKh@0.1"],"first_row_in_archive_order":{"model":"4xRSN-50","paper":"/paper/learning-delicate-local-representations-for","metrics":{"PCKh@0.5":"93"},"code_links":[{"title":"open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose"},{"title":"chenyilun95/tf-cpn","url":"https://github.com/chenyilun95/tf-cpn"},{"title":"caiyuanhao1998/RSN","url":"https://github.com/caiyuanhao1998/RSN"},{"title":"HuangJunJie2017/UDP-Pose","url":"https://github.com/HuangJunJie2017/UDP-Pose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/pose-estimation-on-mpii","task":"Pose Estimation","dataset_variant":"MPII","rows":1,"metrics":["PCKh@0.2"],"first_row_in_archive_order":{"model":"OmniPose (WASPv2)","paper":"/paper/omnipose-a-multi-scale-framework-for-multi","metrics":{"PCKh@0.2":"92.3"},"code_links":[{"title":"bmartacho/OmniPose","url":"https://github.com/bmartacho/OmniPose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/omnipose-a-multi-scale-framework-for-multi","title":"OmniPose: A Multi-Scale Framework for Multi-Person Pose Estimation","date":"2021-03-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/efficientpose-scalable-single-person-pose","title":"EfficientPose: Scalable single-person pose estimation","date":"2020-04-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-delicate-local-representations-for","title":"Learning Delicate Local Representations for Multi-Person Pose Estimation","date":"2020-03-09","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/single-stage-multi-person-pose-machines","title":"Single-Stage Multi-Person Pose Machines","date":"2019-08-24","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/openpose-realtime-multi-person-2d-pose","title":"OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields","date":"2018-12-18","rows_on_this_dataset":1,"code_links":51,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":16,"samples_ran":3,"samples_unverified":13,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-to-refine-human-pose-estimation","title":"Learning to Refine Human Pose Estimation","date":"2018-04-21","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/3d-human-pose-estimation-in-the-wild-by","title":"3D Human Pose Estimation in the Wild by Adversarial Learning","date":"2018-03-26","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/generative-partition-networks-for-multi","title":"Generative Partition Networks for Multi-Person Pose Estimation","date":"2017-05-21","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/arttrack-articulated-multi-person-tracking-in","title":"ArtTrack: Articulated Multi-person Tracking in the Wild","date":"2016-12-05","rows_on_this_dataset":2,"code_links":14,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":29,"samples_ran":1,"samples_unverified":28,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/rmpe-regional-multi-person-pose-estimation","title":"RMPE: Regional Multi-person Pose Estimation","date":"2016-12-01","rows_on_this_dataset":2,"code_links":14,"syntology":null},{"paper":"/paper/realtime-multi-person-2d-pose-estimation","title":"Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields","date":"2016-11-24","rows_on_this_dataset":2,"code_links":61,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":23,"samples_ran":4,"samples_unverified":19,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/associative-embedding-end-to-end-learning-for","title":"Associative Embedding: End-to-End Learning for Joint Detection and Grouping","date":"2016-11-16","rows_on_this_dataset":2,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":0,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multi-person-pose-estimation-with-local-joint","title":"Multi-Person Pose Estimation with Local Joint-to-Person Associations","date":"2016-08-30","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/deepercut-a-deeper-stronger-and-faster-multi","title":"DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model","date":"2016-05-10","rows_on_this_dataset":2,"code_links":16,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":5,"samples_harvested":79,"samples_ran":10,"samples_unverified":69,"pointer_only_for_licence":8,"papers_with_no_sample_that_ran":1,"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."}