MMTalker: Multiresolution 3D Talking Head Synthesis with Multimodal Feature Fusion 文章

arXiv:2604.02941v2 Announce Type: replace Abstract: Speech-driven three-dimensional (3D) facial animation synthesis aims to build a mapping from one-dimensional (1D) speech signals to time-varying 3D facial motion signals. Current methods still face challenges in maintaining lip-sync accuracy and producing realistic facial expressions, primarily due to the highly ill-posed nature of this cross-modal mapping. In this paper, we introduce a novel 3D audio-driven facial animation synthesis method through multi-resolution representation and multi-modal feature fusion, called MMTalker which can accurately reconstruct the rich details of 3D facial motion. We first achieve the continuous representation of 3D face with details by mesh parameterization and non-uniform differentiable sampling. The mesh parameterization technique establishes the correspondence between UV plane and 3D facial mesh and is used to offer ground truth for the continuous learning.