2 citations · 3 across the 4 of their papers we have counts for
5 papers
Ink3D: Sculpting 3D Assets with Extremely Complex Textures via Video Generative Models
Yue Han, Chong Li, Zhening Liu +5
Recent 3D generative models can synthesize high-quality geometry but often struggle to reproduce intricate textures from reference images, largely due to the scarcity of large-scal…
MIMAFace: Face Animation via Motion-Identity Modulated Appearance Feature Learning
Yue Han, Junwei Zhu, Yuxiang Feng +5
Current diffusion-based face animation methods generally adopt a ReferenceNet (a copy of U-Net) and a large amount of curated self-acquired data to learn appearance features, as ro…
Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control
Yue Han, Junwei Zhu, Keke He +7
Current face reenactment and swapping methods mainly rely on GAN frameworks, but recent focus has shifted to pre-trained diffusion models for their superior generation capabilities…
DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation
Qilin Wang, Jiangning Zhang, Chengming Xu +7
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and back…
A Generalist FaceX via Learning Unified Facial Representation
Yue Han, Jiangning Zhang, Junwei Zhu +7
This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously. To achieve this goal, we initially formulate a unified…