{"url":"/dataset/youtube-ugc","name":"YouTube-UGC","full_name":"YouTube UGC dataset","description_markdown":"This YouTube dataset is a sampling from thousands of User Generated Content (UGC) as uploaded to YouTube distributed under the Creative Commons license. This dataset was created in order to assist in the advancement of video compression and quality assessment research of UGC videos.","description_withheld":null,"homepage":"https://media.withyoutube.com/","introduced_date":"2019-04-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/youtube-ugc-dataset-for-video-compression","title":"YouTube UGC Dataset for Video Compression Research","first_author":null,"url":null},"license":{"name":"CC-BY","url":"https://creativecommons.org/licenses/by/3.0/legalcode"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Video Quality Assessment","url":"/task/video-quality-assessment","datasets_with_task":"/datasets/task/video-quality-assessment"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["YouTube-UGC"],"data_loaders":[],"num_papers_in_archive":70,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/video-quality-assessment-on-youtube-ugc","task":"Video Quality Assessment","dataset_variant":"YouTube-UGC","rows":17,"metrics":["PLCC"],"first_row_in_archive_order":{"model":"DOVER (end-to-end)","paper":"/paper/disentangling-aesthetic-and-technical-effects","metrics":{"PLCC":"0.874"},"code_links":[{"title":"vqassessment/dover","url":"https://github.com/vqassessment/dover"},{"title":"QualityAssessment/DOVER","url":"https://github.com/QualityAssessment/DOVER"},{"title":"VQAssessment/FAST-VQA-and-FasterVQA","url":"https://github.com/VQAssessment/FAST-VQA-and-FasterVQA"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/relax-vqa-residual-fragment-and-layer-stack","title":"ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment","date":"2024-07-16","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/disentangling-aesthetic-and-technical-effects","title":"Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives","date":"2022-11-09","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/neighbourhood-representative-sampling-for","title":"Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessment","date":"2022-10-11","rows_on_this_dataset":1,"code_links":4,"syntology":null},{"paper":"/paper/hvs-revisited-a-comprehensive-video-quality","title":"HVS Revisited: A Comprehensive Video Quality Assessment Framework","date":"2022-10-09","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/2bivqa-double-bi-lstm-based-video-quality","title":"2BiVQA: Double Bi-LSTM based Video Quality Assessment of UGC Videos","date":"2022-08-31","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fast-vqa-efficient-end-to-end-video-quality","title":"FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling","date":"2022-07-06","rows_on_this_dataset":2,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":2,"samples_unverified":3,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/conviqt-contrastive-video-quality-estimator","title":"CONVIQT: Contrastive Video Quality Estimator","date":"2022-06-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-deep-learning-based-no-reference-quality","title":"A Deep Learning based No-reference Quality Assessment Model for UGC Videos","date":"2022-04-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/image-quality-assessment-using-contrastive","title":"Image Quality Assessment using Contrastive Learning","date":"2021-10-25","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/chipqa-no-reference-video-quality-prediction","title":"ChipQA: No-Reference Video Quality Prediction via Space-Time Chips","date":"2021-09-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/blindly-assess-quality-of-in-the-wild-videos","title":"Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception","date":"2021-08-19","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/rapique-rapid-and-accurate-video-quality","title":"RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content","date":"2021-01-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/ugc-vqa-benchmarking-blind-video-quality","title":"UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content","date":"2020-05-29","rows_on_this_dataset":1,"code_links":5,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":11,"samples_ran":7,"samples_unverified":4,"pointer_only_for_licence":11,"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."}