{"url":"/dataset/mfsd","name":"MFSD","full_name":"Masked Face Segmentation Dataset","description_markdown":"During the covid-19 era wearing face masks posed new challenges to face-related tasks, including facial recognition, face inpainting, expression\r\nrecognition, and object removal.\r\nMask region segmentation is a preliminary stage to tackle the occlusion issue corresponding to the face-related tasks.\r\nExisting masked face datasets are not procedure binary segmentation maps because Segmenting mask regions manually is a time-consuming operation. As a result, existing unmasking methods;  synthesize training data by overlaying masks on existing face datasets. However, since these techniques rely on an artificially generated mask, their effects tend to seem unnatural. To address this issue, the masked face segmentation dataset(MFSD) provides the first public training dataset for the mask segmentation task.","description_withheld":null,"homepage":"https://github.com/sadjadrz/MFSD","introduced_date":"2024-05-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/abanet-attention-boundary-aware-network-for","title":"ABANet: Attention boundary-aware network for image segmentation","first_author":"Sadjad Rezvani","url":null},"license":{"name":"MIT","url":"https://github.com/sadjadrz/MFSD/?tab=MIT-1-ov-file"},"modalities":[],"tasks":[{"name":"Face Recognition","url":"/task/face-recognition","datasets_with_task":"/datasets/task/face-recognition"},{"name":"Segmentation","url":"/task/segmentation","datasets_with_task":"/datasets/task/segmentation"},{"name":"Facial Inpainting","url":"/task/facial-inpainting","datasets_with_task":"/datasets/task/facial-inpainting"}],"languages":[],"variants":["MFSD"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/segmentation-on-mfsd","task":"Segmentation","dataset_variant":"MFSD","rows":1,"metrics":["F1 Score"],"first_row_in_archive_order":{"model":"ABANet","paper":"/paper/abanet-attention-boundary-aware-network-for","metrics":{"F1 Score":"96.817%"},"code_links":[{"title":"Recognito-Vision/Face-SDK-Linux-Demos","url":"https://github.com/Recognito-Vision/Face-SDK-Linux-Demos"},{"title":"sadjadrz/mfsd","url":"https://github.com/sadjadrz/mfsd"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/abanet-attention-boundary-aware-network-for","title":"ABANet: Attention boundary-aware network for image segmentation","date":"2024-05-17","rows_on_this_dataset":1,"code_links":2,"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."}