FlexiTex: Enhancing Texture Generation with Visual Guidance
Authors: name: DaDong Jiang, name: Xianghui Yang, name: Zibo Zhao, name: Sheng Zhang, name: Jiaao Yu, name: Zeqiang Lai, name: Shaoxiong Yang, name: Chunchao Guo, name: Xiaobo Zhou, name: Zhihui Ke

Recent texture generation methods achieve impressive results due to the
powerful generative prior they leverage from large-scale text-to-image
diffusion models. However, abstract textual prompts are limited in providing
global textural or shape information, which results in the texture generation
methods producing blurry or inconsistent patterns. To tackle this, we present
FlexiTex, embedding rich information via visual guidance to generate a
high-quality texture. The core of FlexiTex is the Visual Guidance Enhancement
module, which incorporates more specific information from visual guidance to
reduce ambiguity in the text prompt and preserve high-frequency details. To
further enhance the visual guidance, we introduce a Direction-Aware Adaptation
module that automatically designs direction prompts based on different camera
poses, avoiding the Janus problem and maintaining semantically global
consistency. Benefiting from the visual guidance, FlexiTex produces
quantitatively and qualitatively sound results, demonstrating its potential to
advance texture generation for real-world applications.