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Found 3 papers, 1 papers with code
Look at Adjacent Frames: Video Anomaly Detection without Offline Training
Based on the information shifts between adjacent frames, an incremental learner is used to update parameters of the multilayer perceptron after observing each frame, thus allowing to detect anomalous events along the video stream.
Video Anomaly Detection via Prediction Network with Enhanced Spatio-Temporal Memory Exchange
Video anomaly detection is a challenging task because most anomalies are scarce and non-deterministic.
Video Anomaly Detection by Estimating Likelihood of Representations
Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but also because it is commonly considered as an unsupervised learning problem that involves detecting outliers.
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