{"url":"/dataset/motion-x","name":"Motion-X","full_name":null,"description_markdown":"Motion-X is a large-scale 3D expressive whole-body motion dataset, which comprises 15.6M precise 3D whole-body pose annotations (i.e., SMPL-X) covering 81.1K motion sequences from massive scenes, meanwhile providing corresponding semantic labels and pose descriptions.","description_withheld":null,"homepage":"https://motion-x-dataset.github.io/","introduced_date":"2023-07-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/motion-x-a-large-scale-3d-expressive-whole","title":"Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset","first_author":"Jing Lin","url":null},"license":{"name":"CC-BYNC-SA 4.0","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"Motion Synthesis","url":"/task/motion-synthesis","datasets_with_task":"/datasets/task/motion-synthesis"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Motion-X"],"data_loaders":[],"num_papers_in_archive":22,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/motion-synthesis-on-motion-x","task":"Motion Synthesis","dataset_variant":"Motion-X","rows":4,"metrics":["FID","TMR-R-Precision Top3","TMR-Matching Score","MModality","Diversity"],"first_row_in_archive_order":{"model":"HumanTOMATO","paper":"/paper/humantomato-text-aligned-whole-body-motion","metrics":{"Diversity":"10.812","FID":"1.174","MModality":"1.732","TMR-Matching Score":"0.809","TMR-R-Precision Top3":"0.703"},"code_links":[{"title":"IDEA-Research/HumanTOMATO","url":"https://github.com/IDEA-Research/HumanTOMATO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/humantomato-text-aligned-whole-body-motion","title":"HumanTOMATO: Text-aligned Whole-body Motion Generation","date":"2023-10-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":18,"samples_ran":12,"samples_unverified":6,"pointer_only_for_licence":18,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/t2m-gpt-generating-human-motion-from-textual","title":"T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations","date":"2023-01-15","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":5,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/executing-your-commands-via-motion-diffusion","title":"Executing your Commands via Motion Diffusion in Latent Space","date":"2022-12-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/human-motion-diffusion-model","title":"Human Motion Diffusion Model","date":"2022-09-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"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":4,"samples_harvested":27,"samples_ran":19,"samples_unverified":8,"pointer_only_for_licence":19,"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."}