{"url":"/dataset/ah36m","name":"AH36M","full_name":"Ambiguous Human3.6M","description_markdown":"Since H36M is captured in a controlled environment, it rarely depicts challenging real-world scenarios such as body occlusions that are the main source of ambiguity in the single-view 3D shape estimation problem. Hence, we construct an adapted version of H36M with synthetically-generated occlusions by randomly hiding a subset of the 2D keypoints and re-computing an image crop around the remaining visible joints.","description_withheld":null,"homepage":"https://sites.google.com/view/3dmb/home","introduced_date":"2020-11-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/3d-multi-bodies-fitting-sets-of-plausible-3d","title":"3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data","first_author":"Benjamin Biggs","url":null},"license":{"name":"MIT","url":"https://github.com/benjiebob/3D-Multibodies/blob/master/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Multi-Hypotheses 3D Human Pose Estimation","url":"/task/multi-hypotheses-3d-human-pose-estimation","datasets_with_task":"/datasets/task/multi-hypotheses-3d-human-pose-estimation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["AH36M"],"data_loaders":[{"repo":"https://github.com/benjiebob/3D-Multibodies","url":"https://github.com/benjiebob/3D-Multibodies","frameworks":["pytorch"]}],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-hypotheses-3d-human-pose-estimation-on-2","task":"Multi-Hypotheses 3D Human Pose Estimation","dataset_variant":"AH36M","rows":10,"metrics":["Best-Hypothesis PMPJPE (n = 25)","H36M PMPJPE (n = 25)","Best-Hypothesis MPJPE (n = 25)","Most-Likely Hypothesis PMPJPE (n = 1)","H36M PMPJPE (n = 1)"],"first_row_in_archive_order":{"model":"MHEntropy (3D)","paper":"/paper/mhentropy-entropy-meets-multiple-hypotheses","metrics":{"Best-Hypothesis MPJPE (n = 25)":"-","Best-Hypothesis PMPJPE (n = 25)":"50.6","H36M PMPJPE (n = 1)":"-","H36M PMPJPE (n = 25)":"36.8","Most-Likely Hypothesis PMPJPE (n = 1)":"-"},"code_links":[{"title":"GloryyrolG/MHEntropy","url":"https://github.com/GloryyrolG/MHEntropy"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/humaniflow-ancestor-conditioned-normalising","title":"HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation","date":"2023-05-11","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":3,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mhentropy-entropy-meets-multiple-hypotheses","title":"MHEntropy: Entropy Meets Multiple Hypotheses for Pose and Shape Recovery","date":"2023-01-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/probabilistic-modeling-for-human-mesh","title":"Probabilistic Modeling for Human Mesh Recovery","date":"2021-08-26","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/3d-multi-bodies-fitting-sets-of-plausible-3d","title":"3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data","date":"2020-11-02","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/generating-multiple-hypotheses-for-3d-human","title":"Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network","date":"2019-04-11","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":1,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/end-to-end-recovery-of-human-shape-and-pose","title":"End-to-end Recovery of Human Shape and Pose","date":"2017-12-18","rows_on_this_dataset":2,"code_links":10,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":17,"samples_ran":4,"samples_unverified":13,"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."}