{"url":"/dataset/lsp","name":"LSP","full_name":"Leeds Sports Pose","description_markdown":"The **Leeds Sports Pose** (**LSP**) dataset is widely used as the benchmark for human pose estimation. The original LSP dataset contains 2,000 images of sportspersons gathered from Flickr, 1000 for training and 1000 for testing. Each image is annotated with 14 joint locations, where left and right joints are consistently labelled from a person-centric viewpoint. The extended LSP dataset contains additional 10,000 images labeled for training.\r\n\r\nSource: [Deep Deformation Network for Object Landmark Localization](https://arxiv.org/abs/1605.01014)\r\n\r\nImage: [Sumer et al](https://www.researchgate.net/figure/Pose-estimation-results-in-Leeds-Sports-Pose-dataset-First-images-are-from-test-set-with_fig3_322058596)","description_withheld":null,"homepage":"https://dbcollection.readthedocs.io/en/latest/datasets/leeds_sports_pose_extended.html","introduced_date":"2010-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation","first_author":null,"url":"https://doi.org/10.5244/C.24.12"},"license":{"name":"Custom","url":"https://ibug.doc.ic.ac.uk/resources/300-W/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"3D Human Pose Estimation","url":"/task/3d-human-pose-estimation","datasets_with_task":"/datasets/task/3d-human-pose-estimation"},{"name":"3D Pose Estimation","url":"/task/3d-pose-estimation","datasets_with_task":"/datasets/task/3d-pose-estimation"}],"languages":[],"variants":["Leeds Sports Poses"," Leeds Sports Pose","LSP"],"data_loaders":[{"repo":"https://github.com/activeloopai/Hub","url":"https://docs.activeloop.ai/datasets/lsp-dataset","frameworks":["tf","pytorch"]},{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/3d_body_mesh.md#lsp","frameworks":["pytorch"]},{"repo":"https://github.com/Graviti-AI/datasets","url":"https://gas.graviti.com/dataset/graviti/LeedsSportsPose","frameworks":["tf","pytorch"]}],"num_papers_in_archive":202,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/pose-estimation-on-leeds-sports-poses","task":"Pose Estimation","dataset_variant":"Leeds Sports Poses","rows":18,"metrics":["PCK"],"first_row_in_archive_order":{"model":"OmniPose","paper":"/paper/omnipose-a-multi-scale-framework-for-multi","metrics":{"PCK":"99.5%"},"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/learning-dynamical-human-joint-affinity-for","title":"Learning Dynamical Human-Joint Affinity for 3D Pose Estimation in Videos","date":"2021-09-15","rows_on_this_dataset":1,"code_links":0,"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/toward-fast-and-accurate-human-pose","title":"Toward fast and accurate human pose estimation via soft-gated skip connections","date":"2020-02-25","rows_on_this_dataset":1,"code_links":3,"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/trajectory-space-factorization-for-deep-video","title":"Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation","date":"2019-08-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fast-human-pose-estimation","title":"Fast Human Pose Estimation","date":"2018-11-13","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/jointly-optimize-data-augmentation-and","title":"Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation","date":"2018-05-24","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/human-pose-regression-by-combining-indirect","title":"Human Pose Regression by Combining Indirect Part Detection and Contextual Information","date":"2017-10-06","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-feature-pyramids-for-human-pose","title":"Learning Feature Pyramids for Human Pose Estimation","date":"2017-08-03","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/self-adversarial-training-for-human-pose","title":"Self Adversarial Training for Human Pose Estimation","date":"2017-07-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/knowledge-guided-deep-fractal-neural-networks","title":"Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation","date":"2017-05-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/vnect-real-time-3d-human-pose-estimation-with","title":"VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera","date":"2017-05-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-context-attention-for-human-pose","title":"Multi-Context Attention for Human Pose Estimation","date":"2017-02-24","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/monocular-3d-human-pose-estimation-in-the","title":"Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision","date":"2016-11-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/human-pose-estimation-via-convolutional-part","title":"Human pose estimation via Convolutional Part Heatmap Regression","date":"2016-09-06","rows_on_this_dataset":1,"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":1,"code_links":16,"syntology":null},{"paper":"/paper/convolutional-pose-machines","title":"Convolutional Pose Machines","date":"2016-01-30","rows_on_this_dataset":1,"code_links":50,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/articulated-pose-estimation-by-a-graphical","title":"Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations","date":"2014-07-12","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":3,"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."}