Attention-Driven Loss for Anomaly Detection in Video Surveillance

• Published in: IEEE transactions on circuits and systems for video technology Vol. 30; no. 12; pp. 4639 - 4647
• Main Authors: Zhou, Joey Tianyi, Zhang, Le, Fang, Zhiwen, Du, Jiawei, Peng, Xi, Xiao, Yang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ablation; Anomalies; Anomaly detection; attention; Computer networks; Convolutional codes; Deep learning; Object recognition; Optimization; Task analysis; Training data

Recent video anomaly detection methods focus on reconstructing or predicting frames. Under this umbrella, the long-standing inter-class data-imbalance problem resorts to the imbalance between foreground and stationary background objects in video anomaly detection and this has been less investigated...