Vocal Visage: Crafting Lifelike 3D Talking Faces from Static Images and Sound

Abstract

In the field of computer graphics and  animation, the challenge of generating lifelike and  expressive talking face animations has historically  necessitated extensive 3D data and complex facial motion  capture systems. However, this project presents an  innovative approach to tackle this challenge, with the  primary goal of producing realistic 3D motion coefficients  for stylized talking face animations driven by a single  reference image synchronized with audio input. Leveraging  state-of-the-art deep learning techniques, including  generative models, image-to-image translation networks,  and audio processing methods, the methodology bridges the  gap between static images and dynamic, emotionally rich  facial animations. The ultimate aim is to synthesize talking  face animations that exhibit seamless lip synchronization  and natural eye blinking, thereby achieving an exceptional  degree of realism and expressiveness, revolutionizing the  realm of computer-generated character interactions.