{"url":"/dataset/lsfb-datasets","name":"LSFB Datasets","full_name":"French Belgian Sign Language Datasets","description_markdown":"# Sign Language Datasets for French Belgian Sign Language\r\nThis dataset is built upon the work of Belgian linguists from the University of Namur. During eight years, they've collected and annotated 50 hours of videos depicting sign language conversation. 100 signers were recorded, making it one of the most representative sign language corpus. \r\nThe annotation has been sanitized and enriched with metadata to construct two, easy to use, datasets for sign language recognition. One for continuous sign language recognition and the other for isolated sign recognition. \r\n\r\n## LSFB-CONT\r\nThe dataset for continuous sign language recognition is made of over 25h of video clips. Each clip is associated with a time-aligned annotation file containing the start and the end of each sign along with a gloss (label) associated with all unique signs. Mediapipe pose and hands information were also computed for each video clip and these metadata are made available in the dataset.\r\n\r\n## LSFB-ISOL\r\nThe isolated version of the dataset contains only clips showing one isolated sign issued from the LSFB-CONT dataset. We chose to keep all the signs with at least 40 examples, leading to a dataset containing over 50 000 clips for 635 different glosses (labels). The Mediapipe metadata is also available for this dataset.","description_withheld":null,"homepage":"https://lsfb.info.unamur.be/","introduced_date":"2021-07-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/lsfb-cont-and-lsfb-isol-two-new-datasets-for","title":"LSFB-CONT and LSFB-ISOL: Two New Datasets for Vision-Based Sign Language Recognition","first_author":"Jérôme Fink","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Sign Language Recognition","url":"/task/sign-language-recognition","datasets_with_task":"/datasets/task/sign-language-recognition"},{"name":"Sign Language Translation","url":"/task/sign-language-translation","datasets_with_task":"/datasets/task/sign-language-translation"},{"name":"Sign Language Production","url":"/task/sign-language-production","datasets_with_task":"/datasets/task/sign-language-production"}],"languages":[{"name":"French","url":"/datasets/language/french"}],"variants":["LSFB Datasets"],"data_loaders":[{"repo":"https://github.com/Jefidev/lsfb-dataset","url":"https://jefidev.github.io/lsfb-dataset/","frameworks":["pytorch"]}],"num_papers_in_archive":1,"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."}