Spatial Attention Transformer Based Framework for Anomaly Classification in Image Sequences

Author:

Garg Aishvarya,Nigam Swati,Singh Rajiv,Shastri Anshuman,Singh Madhusudan

Publisher

Springer Nature Switzerland

Reference42 articles.

1. Franklin, R.J., Dabbagol, V.: Anomaly detection in videos for video surveillance applications using neural networks. In: Fourth International Conference on Inventive Systems and Controls (ICISC), p. 632. IEEE (2020)

2. Anomaly Detection in Videos using LSTM Convolutional Autoencoder, https://towardsdatascience.com/prototyping-an-anomaly-detection-system-for-videos-step-by-step-using-lstm-convolutional-4e06b7dcdd29. Last accessed 25 Apr 2023

3. Garg, A., Nigam, S., Singh, R.: Vision based human activity recognition using hybrid deep learning. In: 2022 International Conference on Connected Systems & Intelligence (CSI), pp. 1–6. IEEE (2022)

4. Berroukham, A., Housni, K., Lahraichi, M., Boulfrifi, I.: Deep learning-based method for anomaly detection in video surveillance: a review. Bull. Electr. Eng. Inf. 2(1), 314–327 (2023)

5. Suarez, J.J.P., Naval Jr, P.C.: A survey on deep learning techniques for video anomaly detection. arXiv preprint arXiv: 2009.14146 (2020)

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