Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

@article{Wang2021RobustUV,
  title={Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction},
  author={X. Wang and Zhengping Che and Ke Yang and Bo Jiang and Jian-Bo Tang and Jieping Ye and Jingyu Wang and Q. Qi},
  journal={IEEE transactions on neural networks and learning systems},
  year={2021},
  volume={PP}
}
  • X. Wang, Zhengping Che, +5 authors Q. Qi
  • Published 5 November 2020
  • Medicine, Computer Science
  • IEEE transactions on neural networks and learning systems
Video anomaly detection is commonly used in many applications, such as security surveillance, and is very challenging. A majority of recent video anomaly detection approaches utilize deep reconstruction models, but their performance is often suboptimal because of insufficient reconstruction error differences between normal and abnormal video frames in practice. Meanwhile, frame prediction-based anomaly detection methods have shown promising performance. In this article, we propose a novel and… 

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