SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection
with Multimodal Large Language Models
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection
with Multimodal Large Language Models
Multimodal large language models (MLLMs) have demonstrated remarkable problem-solving capabilities in various vision fields (e.g., generic object recognition and grounding) based on strong visual semantic representation and language reasoning ability. However, whether MLLMs are sensitive to subtle visual spoof/forged clues and how they perform in the domain of face attack …