GenSync: A Generalized Talking Head Framework for Audio-driven Multi-Subject Lip-Sync using 3D Gaussian Splatting
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Abstract (arXiv)
We introduce GenSync, a novel framework for multi-identity lip-synced video synthesis using 3D Gaussian Splatting. Unlike most existing 3D methods that require training a new model for each identity , GenSync learns a unified network that synthesizes lip-synced videos for multiple speakers. By incorporating a Disentanglement Module, our approach separates identity-specific features from audio representations, enabling efficient multi-identity video synthesis. This design reduces computational overhead and achieves 6.8x faster training compared to state-of-the-art models, while maintaining high lip-sync accuracy and visual quality.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 20 references that are in the map. First posted on arXiv 3 May 2025.
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References · 15
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2020First Order Motion Model for Image Animationcited by 704
- 2021AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesiscited by 339
- 20233DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splattingcited by 195
- 2018X2Face: A network for controlling face generation by using images, audio, and pose codescited by 189
- 2023DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Modelscited by 154
- 2017Morphable Face Models - An Open Frameworkcited by 138
- 2024X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attentioncited by 91
- 2023SyncTalk: The Devil is in the Synchronization for Talking Head Synthesiscited by 86
- 2023Diff2Lip: Audio Conditioned Diffusion Models for Lip-Synchronizationcited by 49
- 2022Masked Lip-Sync Prediction by Audio-Visual Contextual Exploitation in Transformerscited by 33
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