6 papers · 1 filter
MOVA: Towards Scalable and Synchronized Video-Audio Generation
OpenMOSS Team, Donghua Yu, Mingshu Chen +38
Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on casc…
IMTalker: Efficient Audio-driven Talking Face Generation with Implicit Motion Transfer
Bo Chen, Tao Liu, Qi Chen +2
Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail…
Bitrate-Controlled Diffusion for Disentangling Motion and Content in Video
Xiao Li, Qi Chen, Xiulian Peng +3
We propose a novel and general framework to disentangle video data into its dynamic motion and static content components. Our proposed method is a self-supervised pipeline with les…
VQTalker: Towards Multilingual Talking Avatars through Facial Motion Tokenization
Tao Liu, Ziyang Ma, Qi Chen +4
We present VQTalker, a Vector Quantization-based framework for multilingual talking head generation that addresses the challenges of lip synchronization and natural motion across d…
AniTalker: Animate Vivid and Diverse Talking Faces through Identity-Decoupled Facial Motion Encoding
Tao Liu, Feilong Chen, Shuai Fan +4
The paper introduces AniTalker, an innovative framework designed to generate lifelike talking faces from a single portrait. Unlike existing models that primarily focus on verbal cu…
GSTalker: Real-time Audio-Driven Talking Face Generation via Deformable Gaussian Splatting
Bo Chen, Shoukang Hu, Qi Chen +4
We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 35 m…