Contrastive-regularized U-Net for video anomaly detection

Video anomaly detection aims to identify anomalous segments in a video. It is typically trained with weakly supervised video-level labels. This paper focuses on two crucial factors affecting the performance of video anomaly detection models. First, we explore how to capture the local and global temp...

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Bibliographic Details
Main Authors: Gan, Kian Yu, Cheng, Yu Tong, Tan, Hung-Khoon, Ng, Hui-Fuang, Leung, Maylor Karhang, Chuah, Joon Huang
Format: Article
Published: Institute of Electrical and Electronics Engineers 2023
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Online Access:http://eprints.um.edu.my/39002/
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