A Video Face Recognition Leveraging Temporal Information Based on Vision Transformer

Author:

Zhang Hui,Yang Jiewen,Dong Xingbo,Lv Xingguo,Jia Wei,Jin Zhe,Li Xuejun

Publisher

Springer Nature Singapore

Reference33 articles.

1. Arnab, A., Dehghani, M., Heigold, G., Sun, C., Lučić, M., Schmid, C.: Vivit: a video vision transformer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2021)

2. Ballas, N., Yao, L., Pal, C., Courville, A.: Delving deeper into convolutional networks for learning video representations. In: 4th International Conference on Learning Representations, ICLR 2016 (2015)

3. Bertasius, G., Wang, H., Torresani, L.: Is space-time attention all you need for video understanding? In: Proceedings of the International Conference on Machine Learning (ICML), vol. 2, p. 4 (2021)

4. Deng, J., Guo, J., Xue, N., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4690–4699 (2019)

5. Ding, C., Tao, D.: Trunk-branch ensemble convolutional neural networks for video-based face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 1002–1014 (2017)

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