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Research Article | Open Access

TexPro: Text-guided PBR texturing with procedural material modeling

State Key Lab of CAD&CG, Zhejiang University, Hangzhou 310058, China
Pico, ByteDance Inc., Shanghai 200235, China
School of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China

* Ziqiang Dang and Wenqi Dong contributed equally to this work.

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Abstract

In this paper, we present TexPro, a novel method for high-fidelity material generation for input 3D meshes given text prompts. Unlike existing text-conditioned texture generation methods that typically generate RGB textures with baked lighting, TexPro is able to produce diverse texture maps via procedural material modeling, which enables physically-based rendering, relighting, and additional benefits inherent to procedural materials. Specifically, we first generate multi-view reference images given the input textual prompt by employing the latest text-to-image model. We then derive texture maps through rendering-based optimization with recent differentiable procedural materials. To this end, we design several techniques to handle the misalignment between the generated multi-view images and 3D meshes, and introduce a novel material agent that enhances material classification and matching by exploring both part-level understanding and object-aware material reasoning. Experiments demonstrate the superiority of the proposed method over existing SOTAs, and its capability of relighting.

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Computational Visual Media
Pages 745-761

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Cite this article:
Dang Z, Dong W, Yang Z, et al. TexPro: Text-guided PBR texturing with procedural material modeling. Computational Visual Media, 2025, 11(4): 745-761. https://doi.org/10.26599/CVM.2025.9450489

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Received: 13 February 2025
Accepted: 18 April 2025
Published: 01 October 2025
© The Author(s) 2025.

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