Contrastive Learning with Global Representation for Face Anti-spoofing
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5594-3_36
Reference26 articles.
1. Atoum, Y., Liu, Y., Jourabloo, A., Liu, X.: Face anti-spoofing using patch and depth-based CNNs. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), pp. 319–328. IEEE (2017)
2. Bengio, Y., Louradour, J., Collobert, R., Weston, J.: Curriculum learning. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 41–48 (2009)
3. Boulkenafet, Z., Komulainen, J., Hadid, A.: Face anti-spoofing based on color texture analysis. In: 2015 IEEE International Conference on Image Processing (ICIP), pp. 2636–2640. IEEE (2015)
4. Cao, J., Liu, Y., Ding, J., Li, L.: Self-supervised face anti-spoofing via anti-contrastive learning. In: Yu, S., et al. (eds.) Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 479–491. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-18910-4_39
5. de Freitas Pereira, T., Anjos, A., De Martino, J.M., Marcel, S.: Can face anti-spoofing countermeasures work in a real world scenario? In: 2013 International Conference on Biometrics (ICB), pp. 1–8. IEEE (2013)
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