Paint3D：使用无光照纹理扩散模型绘制任意3D物体
Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Models
AI总结：
Paint3D提出从粗到细的生成框架，利用深度感知2D扩散模型与UV修补/UVHD模型，为3D网格生成无光照的高质量2K UV纹理，支持重光照与编辑。
摘要：
本文提出了Paint3D，一种新颖的从粗到细的生成框架，能够为未纹理化的3D网格生成高分辨率、无光照且多样化的2K UV纹理图，其条件为文本或图像输入。所解决的关键挑战是生成不包含嵌入光照信息的高质量纹理，这使得纹理能够在现代图形管线中被重新光照或重新编辑。为实现这一目标，我们的方法首先利用预训练的深度感知2D扩散模型生成视图条件图像，并执行多视图纹理融合，产生初始的粗糙纹理图。然而，由于2D模型无法完全表示3D形状且禁用光照效果，粗糙纹理图表现出不完整区域和光照伪影。为解决此问题，我们训练了专门的UV修补和UVHD扩散模型，分别用于形状感知的不完整区域细化和光照伪影去除。通过这种从粗到细的过程，Paint3D能够生成保持语义一致性且无光照的高质量2K UV纹理，显著推进了3D物体纹理化的最新技术水平。
英文摘要：
This paper presents Paint3D, a novel coarse-to-fine generative framework that is capable of producing high-resolution, lighting-less, and diverse 2K UV texture maps for untextured 3D meshes conditioned on text or image inputs. The key challenge addressed is generating high-quality textures without embedded illumination information, which allows the textures to be re-lighted or re-edited within modern graphics pipelines. To achieve this, our method first leverages a pre-trained depth-aware 2D diffusion model to generate view-conditional images and perform multi-view texture fusion, producing an initial coarse texture map. However, as 2D models cannot fully represent 3D shapes and disable lighting effects, the coarse texture map exhibits incomplete areas and illumination artifacts. To resolve this, we train separate UV Inpainting and UVHD diffusion models specialized for the shape-aware refinement of incomplete areas and the removal of illumination artifacts. Through this coarse-to-fine process, Paint3D can produce high-quality 2K UV textures that maintain semantic consistency while being lighting-less, significantly advancing the state-of-the-art in texturing 3D objects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
