A Lightweight Attention Model for Face Recognition
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50818-9_25
Reference23 articles.
1. Chen, S., Liu, Y., Gao, X., Han, Z.: Mobilefacenets: efficient CNNs for accurate real-time face verification on mobile devices. In: Biometric Recognition: 13th Chinese Conference, CCBR 2018, Urumqi, China, August 11–12, 2018, Proceedings 13, pp. 428–438. Springer (2018)
2. Deng, J., Guo, J., Xue, N., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. In: CVPR, pp. 4690–4699 (2019)
3. Duc, Q.V., Phung, T., Nguyen, M., Nguyen, B.Y., Nguyen, T.H.: Self-knowledge distillation: an efficient approach for falling detection. In: International Conference on Artificial Intelligence and Big Data in Digital Era, pp. 369–380. Springer (2021)
4. Duong, C.N., Luu, K., Quach, K.G., Bui, T.D.: Deep appearance models: a deep Boltzmann machine approach for face modeling. Int. J. Comput. Vis. 127, 437–455 (2019)
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