2 citations · 2 across the 6 of their papers we have counts for
6 papers
StableDub: Taming Diffusion Prior for Generalized and Efficient Visual Dubbing
Liyang Chen, Tianze Zhou, Xu He +7
The visual dubbing task aims to generate mouth movements synchronized with the driving audio, which has seen significant progress in recent years. However, two critical deficiencie…
ProGDF: Progressive Gaussian Differential Field for Controllable and Flexible 3D Editing
Yian Zhao, Wanshi Xu, Yang Wu +3
3D editing plays a crucial role in editing and reusing existing 3D assets, thereby enhancing productivity. Recently, 3DGS-based methods have gained increasing attention due to thei…
GUESS:GradUally Enriching SyntheSis for Text-Driven Human Motion Generation
Xuehao Gao, Yang Yang, Zhenyu Xie +3
In this paper, we propose a novel cascaded diffusion-based generative framework for text-driven human motion synthesis, which exploits a strategy named GradUally Enriching SyntheSi…
Towards Detailed Text-to-Motion Synthesis via Basic-to-Advanced Hierarchical Diffusion Model
Zhenyu Xie, Yang Wu, Xuehao Gao +3
Text-guided motion synthesis aims to generate 3D human motion that not only precisely reflects the textual description but reveals the motion details as much as possible. Pioneerin…
Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
Peng Jin, Yang Wu, Yanbo Fan +3
Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicit…
Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video
Xiuzhe Wu, Pengfei Hu, Yang Wu +6
Synthesizing realistic videos according to a given speech is still an open challenge. Previous works have been plagued by issues such as inaccurate lip shape generation and poor im…