1. Zhao, Y., Deng, B., Shen, C., Liu, Y., Lu, H., & Hua, X.-S. (2017). Spatio-temporal autoencoder for video anomaly detection. In Proceedings of the 25th ACM International Conference on Multimedia (pp. 1933–1941).
2. Pawar, K., & Attar, V. (2019). Deep learning approaches for video-based anomalous activity detection. World Wide Web, 22(2), 571–601.
3. Kiran, B. R., Thomas, D. M., & Parakkal, R. (2018). An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos. Journal of Imaging, 4(2), 36.
4. J.R. Medel, A. Savakis. Anomaly detection in video using predictive convolutional long short-term memory networks. arXiv preprint arXiv:1612.00390 (2016).
5. Luo, W., Liu, W., Lian, D., Tang, J., Duan, L., Peng, X., & Gao, S. (2019). Video anomaly detection with sparse coding inspired deep neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–15.