FlexiTex: Enhancing Texture Generation via Visual Guidance

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.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i4.32415
Primary Topic
Interactive and Immersive Displays
Type
article
Field-Weighted Citation Impact
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article

FlexiTex: Enhancing Texture Generation via Visual Guidance

Sheng Zhang, Chunchao Guo, Zibo Zhao, Zeqiang Lai et al.
Proceedings of the AAAI Conference on Artificial Intelligence
Interactive and Immersive Displays
article

FlexiTex: Enhancing Texture Generation via Visual Guidance

Sheng Zhang, Chunchao Guo, Zibo Zhao, Zeqiang Lai, Jiaao Yu, Xianghui Yang, Zhihui Ke, Shaoxiong Yang, Xiaobo Zhou, Dadong Jiang
article en

Abstract

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.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(4)
Tianjin University (CN), Tencent (China) (CN)
Openalex Percentile: Top 89%
Interactive and Immersive Displays
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FlexiTex: Enhancing Texture Generation via Visual Guidance — Sheng Zhang, Chunchao Guo, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS