{"url":"/dataset/babel-1","name":"BABEL","full_name":null,"description_markdown":"BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL consists of action labels for about 43 hours of mocap sequences from AMASS. Action labels are at two levels of abstraction --  sequence labels describe the overall action in the sequence, and frame labels describe all actions in every frame of the sequence. Each frame label is precisely aligned with the duration of the corresponding action in the mocap sequence, and multiple actions can overlap. There are over 28k sequence labels, and 63k frame labels in BABEL, which belong to over 250 unique action categories. Labels from BABEL can be leveraged for tasks like action recognition, temporal action localization, motion synthesis, etc.","description_withheld":null,"homepage":"https://babel.is.tue.mpg.de/","introduced_date":"2021-06-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/babel-bodies-action-and-behavior-with-english","title":"BABEL: Bodies, Action and Behavior with English Labels","first_author":"Abhinanda R. Punnakkal","url":null},"license":{"name":"Custom","url":"https://babel.is.tue.mpg.de/license.html"},"modalities":[{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"},{"name":"Temporal Action Localization","url":"/task/action-recognition","datasets_with_task":"/datasets/task/action-recognition"},{"name":"3D Action Recognition","url":"/task/3d-human-action-recognition","datasets_with_task":"/datasets/task/3d-human-action-recognition"},{"name":"Action Classification","url":"/task/action-classification","datasets_with_task":"/datasets/task/action-classification"}],"languages":[],"variants":["BABEL"],"data_loaders":[],"num_papers_in_archive":72,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/action-classification-on-babel","task":"Action Classification","dataset_variant":"BABEL","rows":1,"metrics":["CE Top-1","CE Top-1-norm","CE Top-5"],"first_row_in_archive_order":{"model":"2s-AGCN","paper":"/paper/babel-bodies-action-and-behavior-with-english","metrics":{"CE Top-1":"44.87","CE Top-1-norm":"17.16","CE Top-5":"71.78"},"code_links":[{"title":"abhinanda-punnakkal/BABEL","url":"https://github.com/abhinanda-punnakkal/BABEL"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/babel-bodies-action-and-behavior-with-english","title":"BABEL: Bodies, Action and Behavior with English Labels","date":"2021-06-17","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"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."}