{"url":"/dataset/k2hpd","name":"K2HPD","full_name":null,"description_markdown":"Includes 100K depth images under challenging scenarios.\r\n\r\nSource: [Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning](/paper/human-pose-estimation-from-depth-images-via)","description_withheld":null,"homepage":"http://www.sysu-hcp.net/kinect2-human-pose-dataset-k2hpd/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/human-pose-estimation-from-depth-images-via","title":"Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning","first_author":"Keze Wang","url":null},"license":null,"modalities":[],"tasks":[{"name":"Hand Pose Estimation","url":"/task/hand-pose-estimation","datasets_with_task":"/datasets/task/hand-pose-estimation"},{"name":"3D Pose Estimation","url":"/task/3d-pose-estimation","datasets_with_task":"/datasets/task/3d-pose-estimation"}],"languages":[],"variants":["K2HPD"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-pose-estimation-on-k2hpd","task":"3D Pose Estimation","dataset_variant":"K2HPD","rows":1,"metrics":["FPS"],"first_row_in_archive_order":{"model":"A2J","paper":"/paper/a2j-anchor-to-joint-regression-network-for-3d","metrics":{"FPS":"93.78"},"code_links":[{"title":"zhangboshen/A2J","url":"https://github.com/zhangboshen/A2J"},{"title":"bo-zhang-cs/CACNet-Pytorch","url":"https://github.com/bo-zhang-cs/CACNet-Pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/hand-pose-estimation-on-k2hpd","task":"Hand Pose Estimation","dataset_variant":"K2HPD","rows":1,"metrics":["PDJ@5mm"],"first_row_in_archive_order":{"model":"A2J","paper":"/paper/a2j-anchor-to-joint-regression-network-for-3d","metrics":{"PDJ@5mm":"76.3"},"code_links":[{"title":"zhangboshen/A2J","url":"https://github.com/zhangboshen/A2J"},{"title":"bo-zhang-cs/CACNet-Pytorch","url":"https://github.com/bo-zhang-cs/CACNet-Pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a2j-anchor-to-joint-regression-network-for-3d","title":"A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image","date":"2019-08-27","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":0,"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."}