Audio-driven talking head synthesis has achieved impressive progress in lip synchronization and visual quality, yet generating expressive emotional avatars with controllable intensity remains challenging, especially under real-time constraints. In this paper, we present GaussianEmoTalker, an audio-driven framework for real-time emotional talking head synthesis based on 3D Gaussian Splatting.
arXiv:2609.17422v1 Announce Type: new
Abstract: Audio-driven digital human generation plays an important role in virtual communication, immersive interaction, and media production. With the developme...
By Ziheng Yang, Yinfeng Yu, Yongming Li
arXiv:2610.31747v1 Announce Type: new
Abstract: Existing 3D talking avatar methods mainly rely on parametric face models including 3DMM or FLAME, whose compact motion representations limit their abil...
By Zhuoyuan Jiang, Weijie Lyu, Xiaoyuan Wang, Tiancheng Shen, Ming-Hsuan Yang
arXiv:2606.15848v2 Announce Type: replace
Abstract: 3D Gaussian Splatting (3DGS) has shown strong potential for high-fidelity talking head synthesis. However, enabling fine-grained, interpretable, an...
By Tingting Chen, Shaojun Wang, Huaye Zhang, Diqiong Jiang, Chenglizhao Chen
arXiv:2608. 05218v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables fast, photorealistic talking-head rendering, yet accurate lip articulation remains elusive: mouth motion is often over-smoothed and may violate hard articulatory constraints such as bilabial closures, producing the notorious ``leaky mouth'' artifact.
By Ao Fu, Yi Zhou
arXiv:2606. 28568v1 Announce Type: cross Abstract: Speech-driven 3D facial animation methods face significant challenges in simultaneously achieving high-fidelity motion and precise artistic control at production quality.
By Arthur Josi, Emeline Got, Abdallah Dib, Luiz Gustavo Hafemann, Rafael M. O. Cruz