{"url":"/dataset/ubi-fights","name":"UBI-Fights","full_name":"Abnormal Event Detection Dataset","description_markdown":"UBI-Fights - Concerning a specific anomaly detection and still providing a wide diversity in fighting scenarios, the UBI-Fights dataset is a unique new large-scale dataset of 80 hours of video fully annotated at the frame level. Consisting of 1000 videos, where 216 videos contain a fight event, and 784 are normal daily life situations. All unnecessary video segments (e.g., video introductions, news, etc.) that could disturb the learning process were removed.","description_withheld":null,"homepage":"http://socia-lab.di.ubi.pt/EventDetection/","introduced_date":"2021-01-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/iterative-weak-self-supervised-classification","title":"Iterative weak/self-supervised classification framework for abnormal events detection","first_author":"Bruno Degardin","url":null},"license":{"name":"Public","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"},{"name":"Unsupervised Anomaly Detection","url":"/task/unsupervised-anomaly-detection","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection"},{"name":"Anomaly Detection In Surveillance Videos","url":"/task/anomaly-detection-in-surveillance-videos","datasets_with_task":"/datasets/task/anomaly-detection-in-surveillance-videos"},{"name":"Abnormal Event Detection In Video","url":"/task/abnormal-event-detection-in-video","datasets_with_task":"/datasets/task/abnormal-event-detection-in-video"},{"name":"Semi-supervised Anomaly Detection","url":"/task/semi-supervised-anomaly-detection","datasets_with_task":"/datasets/task/semi-supervised-anomaly-detection"},{"name":"Weakly Supervised Classification","url":"/task/weakly-supervised-classification","datasets_with_task":"/datasets/task/weakly-supervised-classification"},{"name":"Semi-Supervised Video Classification","url":"/task/semi-supervised-video-classification","datasets_with_task":"/datasets/task/semi-supervised-video-classification"}],"languages":[],"variants":["UBI-Fights"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semi-supervised-anomaly-detection-on-ubi","task":"Semi-supervised Anomaly Detection","dataset_variant":"UBI-Fights","rows":7,"metrics":["AUC","Decidability","EER"],"first_row_in_archive_order":{"model":"SS-Model + WS-Model + Sultani et al.","paper":"/paper/iterative-weak-self-supervised-classification","metrics":{"AUC":"0.846","Decidability":"1.108","EER":"0.216"},"code_links":[{"title":"DegardinBruno/human_self_learning_anomaly","url":"https://github.com/DegardinBruno/human_self_learning_anomaly"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/abnormal-event-detection-in-video-on-ubi","task":"Abnormal Event Detection In Video","dataset_variant":"UBI-Fights","rows":6,"metrics":["AUC","Decidability","EER"],"first_row_in_archive_order":{"model":"GMM","paper":"/paper/weakly-and-partially-supervised-learning","metrics":{"AUC":"0.906","Decidability":"1.386","EER":"0.160"},"code_links":[{"title":"DegardinBruno/human_self_learning_anomaly","url":"https://github.com/DegardinBruno/human_self_learning_anomaly"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/iterative-weak-self-supervised-classification","title":"Iterative weak/self-supervised classification framework for abnormal events detection","date":"2021-01-03","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/weakly-and-partially-supervised-learning","title":"Weakly and Partially Supervised Learning Frameworks for Anomaly Detection","date":"2020-07-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/generative-neural-networks-for-anomaly","title":"Generative Neural Networks for Anomaly Detection in Crowded Scenes","date":"2018-10-29","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/real-world-anomaly-detection-in-surveillance","title":"Real-world Anomaly Detection in Surveillance Videos","date":"2018-01-12","rows_on_this_dataset":2,"code_links":9,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":4,"samples_unverified":2,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/abnormal-event-detection-in-videos-using-1","title":"Abnormal Event Detection in Videos using Generative Adversarial Nets","date":"2017-08-31","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/abnormal-event-detection-in-videos-using","title":"Abnormal Event Detection in Videos using Spatiotemporal Autoencoder","date":"2017-01-06","rows_on_this_dataset":2,"code_links":5,"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/learning-temporal-regularity-in-video","title":"Learning Temporal Regularity in Video Sequences","date":"2016-04-15","rows_on_this_dataset":2,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":7,"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."}