Fine-tuning Vision-Language Models for Enhanced Face Anti-Spoofing

This research addresses a critical vulnerability in face recognition systems, focusing on improving the detection of presentation attacks. The approach of leveraging vision-language pre-trained models is a promising area of exploration for robust security solutions.

• •The paper explores the application of vision-language models for detecting face presentation attacks.
• •The focus is on incremental learning, allowing for adaptation to new attack types.
• •This research contributes to improving the robustness of face recognition systems against spoofing.