UTDesign: A Unified Framework for Stylized Text Editing and Generation in Graphic Design Images

• URL: http://arxiv.org/abs/2512.20479v1
• Date: Tue, 23 Dec 2025 16:13:55 GMT
• Title: UTDesign: A Unified Framework for Stylized Text Editing and Generation in Graphic Design Images
• Authors: Yiming Zhao, Yuanpeng Gao, Yuxuan Luo, Jiwei Duan, Shisong Lin, Longfei Xiong, Zhouhui Lian,
• Abstract summary: UTDesign is a unified framework for high-precision stylized text editing and conditional text generation in design images.<n>Our framework supports both English and Chinese scripts.<n>It achieves state-of-the-art performance among open-source methods in terms of stylistic consistency and text accuracy.
• Score: 25.895852456869463
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: AI-assisted graphic design has emerged as a powerful tool for automating the creation and editing of design elements such as posters, banners, and advertisements. While diffusion-based text-to-image models have demonstrated strong capabilities in visual content generation, their text rendering performance, particularly for small-scale typography and non-Latin scripts, remains limited. In this paper, we propose UTDesign, a unified framework for high-precision stylized text editing and conditional text generation in design images, supporting both English and Chinese scripts. Our framework introduces a novel DiT-based text style transfer model trained from scratch on a synthetic dataset, capable of generating transparent RGBA text foregrounds that preserve the style of reference glyphs. We further extend this model into a conditional text generation framework by training a multi-modal condition encoder on a curated dataset with detailed text annotations, enabling accurate, style-consistent text synthesis conditioned on background images, prompts, and layout specifications. Finally, we integrate our approach into a fully automated text-to-design (T2D) pipeline by incorporating pre-trained text-to-image (T2I) models and an MLLM-based layout planner. Extensive experiments demonstrate that UTDesign achieves state-of-the-art performance among open-source methods in terms of stylistic consistency and text accuracy, and also exhibits unique advantages compared to proprietary commercial approaches. Code and data for this paper are available at https://github.com/ZYM-PKU/UTDesign.

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