A video anomaly detection method with mask convolution and channel attention
Dawei Yang, Zhiquan Liu, Haiyan Hao · 2023
Aiming at the problem of Insufficient feature extraction for data sets in video anomaly detection, an enhanced detection method combining masked convolution and channel attention is proposed. The auto-encoder structure is adapted, and a mask convolution module and a channel attention module are embedded in the memory model. The effectiveness of the proposed method is demonstrated by comparing the results of the method and the original method.