{"url":"/dataset/m-vad-names","name":"M-VAD Names","full_name":"M-VAD Names Dataset","description_markdown":"The dataset contains the annotations of characters' visual appearances, in the form of tracks of face bounding boxes, and the associations with characters' textual mentions, when available. The detection and annotation of the visual appearances of characters in each video clip of each movie was achieved through a semi-automatic approach. The released dataset contains more than 24k annotated video clips, including 63k visual tracks and 34k textual mentions, all associated with their character identities.\r\n\r\nSource: [M-VAD Names Dataset](https://github.com/aimagelab/mvad-names-dataset)","description_withheld":null,"homepage":"https://github.com/aimagelab/mvad-names-dataset","introduced_date":"2019-03-04","introduced_date_note":null,"introduced_by":{"paper":"/paper/m-vad-names-a-dataset-for-video-captioning","title":"M-VAD Names: a Dataset for Video Captioning with Naming","first_author":"Stefano Pini","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Video Captioning","url":"/task/video-captioning","datasets_with_task":"/datasets/task/video-captioning"},{"name":"Partial Label Learning","url":"/task/partial-label-learning","datasets_with_task":"/datasets/task/partial-label-learning"},{"name":"Gender Prediction","url":"/task/gender-prediction","datasets_with_task":"/datasets/task/gender-prediction"},{"name":"Video Description","url":"/task/video-description","datasets_with_task":"/datasets/task/video-description"}],"languages":[],"variants":["M-VAD Names"],"data_loaders":[{"repo":"https://github.com/aimagelab/mvad-names-dataset","url":"https://github.com/aimagelab/mvad-names-dataset","frameworks":[]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/partial-label-learning-on-m-vad-names","task":"Partial Label Learning","dataset_variant":"M-VAD Names","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"DB-GAE","paper":"/paper/general-partial-label-learning-via-dual","metrics":{"Accuracy":"90.3"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/general-partial-label-learning-via-dual","title":"General Partial Label Learning via Dual Bipartite Graph Autoencoder","date":"2020-01-05","rows_on_this_dataset":1,"code_links":0,"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."}