用多视角扩散融合实现3D模型快速一致的文本贴图生成
MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection
- 通过多视角噪声预测融合与统一去噪方向，保持纹理跨视角一致性
- 相比优化或逐视图合成方法，速度更快且质量更优
- 适合需要高效高质量3D纹理生成的工业设计与游戏开发场景
我们提出MD-ProjTex，一种基于预训练文生图扩散模型的快速、一致的文本引导3D形状贴图生成方法。核心是UV空间中的多视角一致性机制，确保不同视角下纹理连贯。具体而言，MD-ProjTex在每个扩散步骤融合多个视图的噪声预测，并联合更新各视图的去噪方向以维持3D一致性。与依赖优化或顺序视图合成的现有最优方法相比，MD-ProjTex计算效率更高，且在定量与定性指标上均表现更优。
原文摘要 · Abstract (English)
We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which ensures coherent textures across different viewpoints. Specifically, MD-ProjTex fuses noise predictions from multiple views at each diffusion step and jointly updates the per-view denoising directions to maintain 3D consistency. In contrast to existing state-of-the-art methods that rely on optimization or sequential view synthesis, MD-ProjTex is computationally more efficient and achieves better quantitative and qualitative results.
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