{"url":"/dataset/tv-ad","name":"TV-AD","full_name":"Audio Description dataset for TV series","description_markdown":"TV-AD is a dataset that provides ground truth AD annotations that are aligned with TV series video, featuring episodes across multiple TV series including “The Big Bang Theory”, “Friends”, “Frasier”, “Seinfeld”, etc. The dataset is divided into training (TV-AD-Train, ∼31k ADs) and evaluation splits (TV-AD-Eval, ∼3k ADs), ensuring that the TV series do not overlap between the two splits. The evaluation split contains AD annotations for TV videos that are publicly available.","description_withheld":null,"homepage":"https://www.robots.ox.ac.uk/~vgg/research/autoad-zero/#tvad","introduced_date":"2024-07-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/autoad-zero-a-training-free-framework-for","title":"AutoAD-Zero: A Training-Free Framework for Zero-Shot Audio Description","first_author":"Junyu Xie","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["TV-AD"],"data_loaders":[],"num_papers_in_archive":3,"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."}