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. Code is available at https://cvmi-lab.github.io/Point-UV-Diffusion

翻译：本研究聚焦于在三维网格上合成高质量纹理。我们提出点-UV扩散方法（Point-UV diffusion），这是一种从粗到细的处理流程，将去噪扩散模型与UV映射相结合，在UV空间中生成具有三维一致性的高质量纹理图像。首先引入点扩散模型，通过我们设计的风格引导机制，生成低频纹理分量以解决颜色分布偏差问题。由此得到的粗纹理提供全局一致性，并为后续UV扩散阶段提供条件，从而约束模型生成具有三维一致性的UV纹理图像。随后，我们开发了具有混合条件的UV扩散模型，用于在二维UV空间中提升纹理保真度。本方法可处理任意亏格的三维网格，生成多样化、几何兼容且高保真度的纹理。代码开源地址：https://cvmi-lab.github.io/Point-UV-Diffusion