{"url":"/dataset/mocapact","name":"MoCapAct","full_name":"Motion Capture with Actions","description_markdown":"The MoCapAct dataset contains training data and models for humanoid locomotion research. It consists of expert policies that are trained to track individual clip snippets and HDF5 files of noisy rollouts collected from each expert, including proprioceptive observations and actions.","description_withheld":null,"homepage":"https://github.com/microsoft/MoCapAct#dataset","introduced_date":"2022-08-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/mocapact-a-multi-task-dataset-for-simulated","title":"MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control","first_author":"Nolan Wagener","url":null},"license":{"name":"CDLA Permissive 2.0","url":"https://cdla.dev/permissive-2-0/"},"modalities":[],"tasks":[{"name":"Continuous Control","url":"/task/continuous-control","datasets_with_task":"/datasets/task/continuous-control"},{"name":"Human motion prediction","url":"/task/human-motion-prediction","datasets_with_task":"/datasets/task/human-motion-prediction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["MoCapAct"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"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."}