Texture Generation on 3D Meshes with Point-UV Diffusion

Xin Yu, Peng Dai, Wenbo Li, Lan Ma, Zhengzhe Liu, Xiaojuan Qi; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 4206-4216

Abstract


In this work, we focus on synthesizing high-quality textures on 3D meshes. We present Point-UV diffusion, a coarse-to-fine pipeline that marries the denoising diffusion model with UV mapping to generate 3D consistent and high-quality texture images in UV space. We start with introducing a point diffusion model to synthesize low-frequency texture components with our tailored style guidance to tackle the biased color distribution. The derived coarse texture offers global consistency and serves as a condition for the subsequent UV diffusion stage, aiding in regularizing the model to generate a 3D consistent UV texture image. Then, a UV diffusion model with hybrid conditions is developed to enhance the texture fidelity in the 2D UV space. Our method can process meshes of any genus, generating diversified, geometry-compatible, and high-fidelity textures.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Yu_2023_ICCV, author = {Yu, Xin and Dai, Peng and Li, Wenbo and Ma, Lan and Liu, Zhengzhe and Qi, Xiaojuan}, title = {Texture Generation on 3D Meshes with Point-UV Diffusion}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {4206-4216} }