COVAD: Content-oriented video anomaly detection using a self attention-based deep learning model
Video anomaly detection is a research hotspot in the field of computer vision, attracting many researchers.Video anomaly detection differs from traditional video analysis. Usually, abnormal events occur only in a small percentage of the video pixels and therefore, it is unnecessary to focus on all the video pixels as most of
them are harmless—called “the background”. Therefore, in the video feature extraction process, attention should be focused on a few detectable partial objects. Object detection is very complicated and consumes a significant amount of time during video processing. Therefore, ...












