MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection
Abstract
MD-ProjTex efficiently generates consistent text-guided textures for 3D shapes using noise fusion and joint denoising in UV space, outperforming existing methods.
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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