5 papers
OMGTex: One-stage Multi-style Facial Texture Reconstruction without Geometry Guidance
Zitong Xiao, Yuda Qiu, Zisheng Ye +1
We propose OMGTex, an end-to-end diffusion-based framework for reconstructing high-quality and editable facial UV textures from multi-style facial images. Existing texture reconstr…
HairOrbit: Multi-view Aware 3D Hair Modeling from Single Portraits
Leyang Jin, Yujian Zheng, Bingkui Tong +3
Reconstructing strand-level 3D hair from a single-view image is highly challenging, especially when preserving consistent and realistic attributes in unseen regions. Existing metho…
TexSpot: 3D Texture Enhancement with Spatially-uniform Point Latent Representation
Ziteng Lu, Yushuang Wu, Chongjie Ye +7
High-quality 3D texture generation remains a fundamental challenge due to the view-inconsistency inherent in current mainstream multi-view diffusion pipelines. Existing representat…
Condition Matters in Full-head 3D GANs
Heyuan Li, Huimin Zhang, Yuda Qiu +10
Conditioning is crucial for stable training of full-head 3D GANs. Without any conditioning signal, the model suffers from severe mode collapse, making it impractical to training. H…
AvatarTex: High-Fidelity Facial Texture Reconstruction from Single-Image Stylized Avatars
Yuda Qiu, Zitong Xiao, Yiwei Zuo +3
We present AvatarTex, a high-fidelity facial texture reconstruction framework capable of generating both stylized and photorealistic textures from a single image. Existing methods…