{"url":"/dataset/bedlam","name":"BEDLAM","full_name":null,"description_markdown":"**BEDLAM** is a large-scale synthetic video dataset designed to train and test algorithms on the task of 3D human pose and shape estimation (HPS). It contains diverse body shapes, skin tones, and motions. The clothing is realistically simulated on the moving bodies using commercial clothing physics simulation.","description_withheld":null,"homepage":"https://bedlam.is.tue.mpg.de/#data","introduced_date":"2023-06-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/bedlam-a-synthetic-dataset-of-bodies-1","title":"BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion","first_author":"Michael J. Black","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"3D Human Pose Estimation","url":"/task/3d-human-pose-estimation","datasets_with_task":"/datasets/task/3d-human-pose-estimation"},{"name":"3D Human Shape Estimation","url":"/task/3d-human-shape-estimation","datasets_with_task":"/datasets/task/3d-human-shape-estimation"},{"name":"Human Mesh Recovery","url":"/task/human-mesh-recovery","datasets_with_task":"/datasets/task/human-mesh-recovery"}],"languages":[],"variants":["BEDLAM"],"data_loaders":[],"num_papers_in_archive":45,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/human-mesh-recovery-on-bedlam","task":"Human Mesh Recovery","dataset_variant":"BEDLAM","rows":3,"metrics":["PVE-All"],"first_row_in_archive_order":{"model":"Multi-HMR","paper":"/paper/multi-hmr-multi-person-whole-body-human-mesh","metrics":{"PVE-All":"76.80"},"code_links":[{"title":"naver/multi-hmr","url":"https://github.com/naver/multi-hmr"}]},"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/cliff-carrying-location-information-in-full","title":"CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation","date":"2022-08-01","rows_on_this_dataset":2,"code_links":6,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"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":2,"samples_harvested":12,"samples_ran":8,"samples_unverified":4,"pointer_only_for_licence":9,"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."}