{"url":"/dataset/vgg-sound-sync","name":"VGG-Sound Sync","full_name":null,"description_markdown":"**VGG-Sound Sync** is an audio-visual synchronisation benchmark based on videos collected from YouTube. VGG-Sound Sync contains over 100k video clips, spanning 160 classes and can be downloaded [here](https://www.robots.ox.ac.uk/~vgg/research/avs/data/vggsoundsync.csv).\r\n\r\nNote, only the test clips are included here, please use the training clips in the original [VGG-Sound](https://paperswithcode.com/dataset/vgg-sound) to train your models ( classes are same with the ones in the test clips). Each line in the json file has been defined by:\r\n\r\n`# YouTube ID, start seconds, label `","description_withheld":null,"homepage":"https://www.robots.ox.ac.uk/~vgg/research/avs/","introduced_date":"2021-12-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/audio-visual-synchronisation-in-the-wild","title":"Audio-Visual Synchronisation in the wild","first_author":"Honglie Chen","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[],"languages":[],"variants":["VGG-Sound Sync"],"data_loaders":[],"num_papers_in_archive":2,"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":"2026-09-25T09:33:49+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."}