Unbiased multiple instance learning for weakly supervised video anomaly detection

• المؤلفون الرئيسيون: Lv, Hui, Yue, Zhongqi, Sun, Qianru, Luo, Bin, Cui, Zhen, Zhang, Hanwang
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Multiple Instance Learning; Weakly Supervised Video Anomaly Detection
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/169509; https://cvpr2023.thecvf.com/Conferences/2023

Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the binary anomaly label is only given on the video level, but the output requires snippetlevel predictions. So, Multiple Instance Learning (MIL) is prevailing in WSVAD. However, MIL is notoriously known to suffer from man...