How AI describes IDiff-Face

IDiff-Face is a synthetic face recognition approach that uses conditional latent diffusion models to generate realistic identity variations for training face recognition systems. It achieves 98.00% accuracy on the LFW benchmark, significantly outperforming other synthetic-based methods and narrowing the gap with authentic data-trained models.