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CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-spoofing
March 22, 2024, 4:45 a.m. | Ajian Liu, Shuai Xue, Jianwen Gan, Jun Wan, Yanyan Liang, Jiankang Deng, Sergio Escalera, Zhen Lei
cs.CV updates on arXiv.org arxiv.org
Abstract: Domain generalization (DG) based Face Anti-Spoofing (FAS) aims to improve the model's performance on unseen domains. Existing methods either rely on domain labels to align domain-invariant feature spaces, or disentangle generalizable features from the whole sample, which inevitably lead to the distortion of semantic feature structures and achieve limited generalization. In this work, we make use of large-scale VLMs like CLIP and leverage the textual feature to dynamically adjust the classifier's weights for exploring generalizable …
abstract arxiv class cs.cv domain domains face feature features free labels performance prompt prompt learning sample semantic spaces s performance type
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