Video Prediction and Anomaly Detection Algorithm Based On Dual Discriminator

Abstract

In order to make full use of the useful information in the massive video data and provide early warning of abnormal events, we propose a video prediction and abnormal detection algorithm. The algorithm designed a generation adversarial network with a single generator and dual discriminator to predict the video, and then performs anomaly detection on the basis of the video prediction frame. For training the model, various loss functions such as perceptual loss and optical flow loss are added to constrain the network. Extensive experiments on three publicly available datasets validate the effectiveness of our method in terms of various evaluation criteria.