Fake Face

Fake face generation, using AI techniques like GANs and diffusion models, poses significant challenges to information security and societal trust. Current research focuses on improving the detection of these synthetic faces, employing methods that analyze visual features (e.g., frequency analysis, facial region displacement), perceptual fidelity, and even leveraging multimodal large language models for explainable analysis. These advancements are crucial for mitigating the risks associated with deepfakes and other forms of AI-generated misinformation, impacting fields ranging from cybersecurity to media verification.