69 citations · 115 across the 29 of their papers we have counts for
9 papers · 1 filter
StyleTalk++: A Unified Framework for Controlling the Speaking Styles of Talking Heads
Suzhen Wang, Yifeng Ma, Yu Ding +5
Individuals have unique facial expression and head pose styles that reflect their personalized speaking styles. Existing one-shot talking head methods cannot capture such personali…
Towards a Simultaneous and Granular Identity-Expression Control in Personalized Face Generation
Renshuai Liu, Bowen Ma, Wei Zhang +5
In human-centric content generation, the pre-trained text-to-image models struggle to produce user-wanted portrait images, which retain the identity of individuals while exhibiting…
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation
Haowei Wang, Jiji Tang, Jiayi Ji +8
In recent years, 3D understanding has turned to 2D vision-language pre-trained models to overcome data scarcity challenges. However, existing methods simply transfer 2D alignment s…
FlowFace++: Explicit Semantic Flow-supervised End-to-End Face Swapping
Yu Zhang, Hao Zeng, Bowen Ma +5
This work proposes a novel face-swapping framework FlowFace++, utilizing explicit semantic flow supervision and end-to-end architecture to facilitate shape-aware face-swapping. Spe…
TalkCLIP: Talking Head Generation with Text-Guided Expressive Speaking Styles
Yifeng Ma, Suzhen Wang, Yu Ding +6
Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to…
DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video
Zhimeng Zhang, Zhipeng Hu, Wenjin Deng +3
For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity du…