… In this paper, since prediction and reconstruction methods have their own advantages and
disadvantages respectively in anomaly detection, we propose an approach that integrates …

… reconstruction of the same sample or the prediction of future samples. Therefore, we
record the reconstruction or prediction … In particular, during inference, if the reconstruction/prediction …

… In this paper, rather than reconstructing training data for anomaly detection, we propose to …
frame prediction based anomaly detection method. Specifically, given a video clip, we predict …

… In this paper, since the quality of future frame prediction is vital for anomaly detection, we
propose a practical prediction module by adding HDC and DB-ConvLSTM strategies to capture …

… age future prediction for anomaly detection. Compared with reconstruction, future prediction
is more sensitive for local and contextual anomalies since they are hard to be predicted. …

… that integrates Flow reconstruction and Frame prediction seamlessly to handle Video
Anomaly Detection. Firstly, we … Finally, we show how to use our model for anomaly detection. …

… -training the prediction and reconstruction module can contribute … anomalous detector can
further improve the performance. The proposed MORPH-Net’s prediction and reconstruction …

… Abstract—Anomaly detection in videos is a significant yet challenging problem. Previous
approaches based on deep neural networks employ either reconstruction-based or prediction-…

… —Video Anomaly detection in … of reconstruction errors of training data including only normal
events, which may lead to self-reconstruction and cannot guarantee a larger reconstruction …

… methods, which decomposes reconstruction into prediction and refinement stages. By … for
anomaly detection. In the refinement stage, we introduce ERM to reconstruct prediction error …