TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling

TL;DR

TexGen introduces a multi-view sampling and resampling framework leveraging a pre-trained text-to-image diffusion model to generate high-quality, view-consistent 3D textures from textual descriptions, outperforming existing methods.

Contribution

The paper presents a novel multi-view sampling and noise resampling framework for 3D texture generation that enhances view consistency and texture detail preservation using diffusion models.

Findings

Produces significantly better texture quality than state-of-the-art methods.

Ensures high view consistency and rich appearance details.

Applicable to texture editing while maintaining original identity.

Abstract

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle these issues, we present TexGen, a novel multi-view sampling and resampling framework for texture generation leveraging a pre-trained text-to-image diffusion model. For view consistent sampling, first of all we maintain a texture map in RGB space that is parameterized by the denoising step and updated after each sampling step of the diffusion model to progressively reduce the view discrepancy. An attention-guided multi-view sampling strategy is exploited to broadcast the appearance information across views. To preserve texture details, we develop a noise resampling technique that aids in the estimation of noise, generating inputs for subsequent denoising steps, as directed by the text prompt and current texture map. Through an extensive amount of qualitative and quantitative evaluations, we demonstrate that our proposed method produces significantly better texture quality for diverse 3D objects with a high degree of view consistency and rich appearance details, outperforming current state-of-the-art methods. Furthermore, our proposed texture generation technique can also be applied to texture editing while preserving the original identity. More experimental results are available at https://dong-huo.github.io/TexGen/