Test-Time Domain Generalization for Face Anti-Spoofing

arXiv:2403.19334v1 Announce Type: new
Abstract: Face Anti-Spoofing (FAS) is pivotal in safeguarding facial recognition systems against presentation attacks. While domain generalization (DG) methods have been developed to enhance FAS performance, they predominantly focus on learning domain-invariant features during training, which may not guarantee generalizability to unseen data that differs largely from the source distributions. Our insight is that testing data can serve as a valuable resource to enhance the generalizability beyond mere evaluation for DG FAS. In this paper, we …

abstract arxiv attacks cs.cv data domain face facial recognition features focus performance pivotal presentation recognition systems test training type