{"url":"/dataset/penn-action","name":"Penn Action","full_name":null,"description_markdown":"The **Penn Action** Dataset contains 2326 video sequences of 15 different actions and human joint annotations for each sequence.\r\n\r\nSource: [http://dreamdragon.github.io/PennAction/](http://dreamdragon.github.io/PennAction/)\r\nImage Source: [http://dreamdragon.github.io/PennAction/](http://dreamdragon.github.io/PennAction/)","description_withheld":null,"homepage":"http://dreamdragon.github.io/PennAction/","introduced_date":"2013-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"From Actemes to Action: A Strongly-Supervised Representation for Detailed Action Understanding","first_author":null,"url":"https://doi.org/10.1109/ICCV.2013.280"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"},{"name":"Skeleton Based Action Recognition","url":"/task/skeleton-based-action-recognition","datasets_with_task":"/datasets/task/skeleton-based-action-recognition"},{"name":"Video Alignment","url":"/task/video-alignment","datasets_with_task":"/datasets/task/video-alignment"}],"languages":[],"variants":["UPenn Action","Penn Action"],"data_loaders":[],"num_papers_in_archive":110,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/pose-estimation-on-upenn-action","task":"Pose Estimation","dataset_variant":"UPenn Action","rows":5,"metrics":["Mean PCK@0.2"],"first_row_in_archive_order":{"model":"OmniPose","paper":"/paper/omnipose-a-multi-scale-framework-for-multi","metrics":{"Mean PCK@0.2":"99.4"},"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"},{"leaderboard":"/sota/video-alignment-on-upenn-action","task":"Video Alignment","dataset_variant":"UPenn Action","rows":4,"metrics":["Kendall's Tau"],"first_row_in_archive_order":{"model":"TCC + TCN","paper":"/paper/temporal-cycle-consistency-learning","metrics":{"Kendall's Tau":"0.7672"},"code_links":[{"title":"google-research/google-research","url":"https://github.com/google-research/google-research/tree/master/tcc"},{"title":"June01/tcc_Temporal_Cycle_Consistency_Loss.pytorch","url":"https://github.com/June01/tcc_Temporal_Cycle_Consistency_Loss.pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/skeleton-based-action-recognition-on-upenn","task":"Skeleton Based Action Recognition","dataset_variant":"UPenn Action","rows":3,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"UNIK","paper":"/paper/unik-a-unified-framework-for-real-world","metrics":{"Accuracy":"97.9"},"code_links":[{"title":"YangDi666/UNIK","url":"https://github.com/YangDi666/UNIK"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/action-recognition-on-penn-action","task":"Action Recognition","dataset_variant":"Penn Action","rows":2,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"3DA (RGB + Pose)","paper":"/paper/cross-modal-learning-with-3d-deformable","metrics":{"Accuracy":"99.7"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cross-modal-learning-with-3d-deformable","title":"Cross-Modal Learning with 3D Deformable Attention for Action Recognition","date":"2022-12-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/star-transformer-a-spatio-temporal-cross-1","title":"STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition","date":"2022-10-14","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/unik-a-unified-framework-for-real-world","title":"UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition","date":"2021-07-19","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"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/unipose-unified-human-pose-estimation-in","title":"UniPose: Unified Human Pose Estimation in Single Images and Videos","date":"2020-01-22","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/view-invariant-probabilistic-embedding-for","title":"View-Invariant Probabilistic Embedding for Human Pose","date":"2019-12-02","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/bayesian-hierarchical-dynamic-model-for-human","title":"Bayesian Hierarchical Dynamic Model for Human Action Recognition","date":"2019-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/temporal-cycle-consistency-learning","title":"Temporal Cycle-Consistency Learning","date":"2019-04-16","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":0,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/lstm-pose-machines","title":"LSTM Pose Machines","date":"2017-12-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/time-contrastive-networks-self-supervised","title":"Time-Contrastive Networks: Self-Supervised Learning from Video","date":"2017-04-23","rows_on_this_dataset":1,"code_links":7,"syntology":null},{"paper":"/paper/thin-slicing-network-a-deep-structured-model","title":"Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos","date":"2017-03-31","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/pose-for-action-action-for-pose","title":"Pose for Action - Action for Pose","date":"2016-03-13","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":12,"samples_ran":0,"samples_unverified":12,"pointer_only_for_licence":0,"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."}