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Tianjin Municipal Education Commission
Reference87 articles.
1. Acsintoae, A., Florescu, A., Georgescu, M., Mare, T., Sumedrea, P., Ionescu, R. T., et al. (2022). UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection. In IEEE conference on computer vision and pattern recognition, CVPR (pp. 20111–20121).
2. SSMTL++: Revisiting self-supervised multi-task learning for video anomaly detection;Barbalau,2022
3. Bogdoll, D., Nitsche, M., & Zöllner, J. M. (2022). Anomaly detection in autonomous driving: A survey. In IEEE conference on computer vision and pattern recognition, CVPR (pp. 4488–4499).
4. Adaptive graph convolutional networks for weakly supervised anomaly detection in videos;Cao;IEEE Signal Processing Letters,2022
5. Carreira, J., & Zisserman, A. (2017). Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. In IEEE conference on computer vision and pattern recognition, CVPR (pp. 4724–4733).