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Although what is considered abnormal depends on the context, we can generally agree that abnormal events should be unexpected events that occur less often than familiar (normal) events\r\n\r\n\r\n<span class=\"description-source\">Source: [Unmasking the abnormal events in video ](https://arxiv.org/abs/1705.08182)</span>\r\n\r\nImage: [Ravanbakhsh et al](https://arxiv.org/pdf/1708.09644v1.pdf)","categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":17,"papers_with_code":13,"benchmarks":2,"benchmark_tables_in_archive":2,"benchmark_tables_shown":2,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":4,"subtasks":1,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/abnormal-event-detection-in-video-on-ubi","slug":"abnormal-event-detection-in-video-on-ubi","dataset":"UBI-Fights","dataset_url":"/dataset/ubi-fights","rows_in_archive":6,"metrics":["AUC","Decidability","EER"],"first_row_in_archive_order":{"model":"GMM","paper_title":"Weakly and Partially Supervised Learning Frameworks for Anomaly Detection","paper_url":"/paper/weakly-and-partially-supervised-learning","paper_date":"2020-07-23","arxiv_id":null,"code_links":[{"title":"DegardinBruno/human_self_learning_anomaly","url":"https://github.com/DegardinBruno/human_self_learning_anomaly"}],"syntology":null}},{"leaderboard":"/sota/abnormal-event-detection-in-video-on-ucsd","slug":"abnormal-event-detection-in-video-on-ucsd","dataset":"UCSD Ped2","dataset_url":"/dataset/ucsd","rows_in_archive":4,"metrics":["AUC"],"first_row_in_archive_order":{"model":"AI-VAD","paper_title":"An Attribute-based Method for Video Anomaly Detection","paper_url":"/paper/attribute-based-representations-for-accurate","paper_date":"2022-12-01","arxiv_id":"2212.00789","code_links":[{"title":"openvinotoolkit/anomalib","url":"https://github.com/openvinotoolkit/anomalib/tree/main/src/anomalib/models/ai_vad"},{"title":"talreiss/Mean-Shifted-Anomaly-Detection","url":"https://github.com/talreiss/Mean-Shifted-Anomaly-Detection"},{"title":"talreiss/accurate-interpretable-vad","url":"https://github.com/talreiss/accurate-interpretable-vad"},{"title":"talreiss/PANDA","url":"https://github.com/talreiss/PANDA"}],"syntology":{"n":3,"n_ran":2,"n_unverified":1,"n_pointer_only":3}}}],"datasets":[{"url":"/dataset/shanghaitech","name":"ShanghaiTech","full_name":"","num_papers_in_archive":277},{"url":"/dataset/shanghaitech-campus","name":"ShanghaiTech Campus","full_name":"","num_papers_in_archive":207},{"url":"/dataset/ucsd","name":"UCSD Ped2","full_name":"UCSD Anomaly Detection Dataset","num_papers_in_archive":92},{"url":"/dataset/ubi-fights","name":"UBI-Fights","full_name":"Abnormal Event Detection Dataset","num_papers_in_archive":7}],"subtasks":[{"url":"/task/semi-supervised-anomaly-detection","name":"Semi-supervised Anomaly Detection"}],"parent_tasks":[{"url":"/task/anomaly-detection","name":"Anomaly Detection"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); 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