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S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens

Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on deep learning models but their cross-domain generalization capabilities are often hindered by the domain shift problem, which arises due to different distributions between training and testing data.

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Cite this as

Rizhao Cai, Zitong Yu, Chenqi Kong, Haoliang Li, Changsheng Chen, Yongjian Hu, Alex C. Kot (2024). Dataset: S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens. https://doi.org/10.57702/uzzdf233

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Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Rizhao Cai
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Zitong Yu
Chenqi Kong
Haoliang Li
Changsheng Chen
Yongjian Hu
Alex C. Kot