Source Face

Source face manipulation research focuses on realistically transferring facial attributes (expressions, poses, even identities) between images or videos, aiming for high-fidelity results that preserve source identity and avoid artifacts. Current efforts utilize advanced techniques like generative adversarial networks (GANs), neural radiance fields (NeRFs), and transformers, often incorporating 3D facial models for improved accuracy and robustness, particularly with challenging poses and resolutions. This field is significant for applications in video editing, animation, and even forensic science, with ongoing improvements driving progress in image synthesis and manipulation.