FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models

arXiv:2312.08459v2 Announce Type: replace
Abstract: We introduce FaceTalk, a novel generative approach designed for synthesizing high-fidelity 3D motion sequences of talking human heads from input audio signal. To capture the expressive, detailed nature of human heads, including hair, ears, and finer-scale eye movements, we propose to couple speech signal with the latent space of neural parametric head models to create high-fidelity, temporally coherent motion sequences. We propose a new latent diffusion model for this task, operating in the expression space …

abstract arxiv audio cs.ai cs.cv cs.gr cs.sd diffusion eess.as fidelity generative hair head human movements nature novel parametric scale signal speech type