AI RESEARCH
Benchmarking Vision Foundation Models for Domain-Generalizable Face Anti-Spoofing
arXiv CS.CV
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ArXi:2604.19196v1 Announce Type: new Face Anti-Spoofing (FAS) remains challenging due to the requirement for robust domain generalization across unseen environments. While recent trends leverage Vision-Language Models (VLMs) for semantic supervision, these multimodal approaches often demand prohibitive computational resources and exhibit high inference latency. Furthermore, their efficacy is inherently limited by the quality of the underlying visual features. This paper revisits the potential of vision-only foundation models to establish a highly efficient and robust baseline for