Text-to-texture generation has recently attracted increasing attention, but existing methods often suffer from the problems of view inconsistencies, apparent seams, and misalignment between textures and the underlying mesh. In this paper, we propose a robust text-to-texture method for generating consistent and seamless textures that are well aligned with the mesh. Our method leverages state-of-the-art 2D diffusion models, including SDXL and multiple ControlNets, to capture structural features and intricate details in the generated textures. The method also employs a symmetrical view synthesis strategy combined with regional prompts for enhancing view consistency. Additionally, it introduces novel texture blending and soft-inpainting techniques, which significantly reduce the seam regions. Extensive experiments demonstrate that our method outperforms existing state-of-the-art methods.

本文针对现有文本到纹理生成方法中的视角不一致和纹理与网格不对齐等问题，提出了一种强健的文本到纹理生成方法。该方法利用先进的2D扩散模型，结合对称视图合成策略和区域提示，显著提升了生成纹理的一致性和无缝性，实验证明其在性能上优于现有的最先进方法。

RoCoTex：一种基于扩散模型的强健一致纹理合成方法