Unbiased multiple instance learning for weakly supervised video anomaly detection

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...

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Bibliographic Details
Main Authors: Lv, Hui, Yue, Zhongqi, Sun, Qianru, Luo, Bin, Cui, Zhen, Zhang, Hanwang
Other Authors: School of Computer Science and Engineering
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/169509
https://cvpr2023.thecvf.com/Conferences/2023
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Institution: Nanyang Technological University
Language: English