Facial Expression Transfer

Facial expression transfer aims to realistically transfer expressions from one face to another, often for applications in animation or video editing. Current research focuses on improving the accuracy and realism of transferred expressions, employing techniques like neural radiance fields (NeRFs), generative adversarial networks (GANs), and transformer-based architectures to achieve disentangled representations of identity and expression. These advancements leverage both 2D and 3D facial models, incorporating geometric information and perceptual constraints to generate high-fidelity results, addressing limitations in handling extreme poses and complex backgrounds. The field's progress has significant implications for creating more expressive and realistic avatars in virtual and augmented reality, as well as for applications in film and animation.