VogFashion: an AI-driven intelligent system for fashion design

Artificial Intelligence (AI) technologies have demonstrated significant potential in fashion design. Designers can leverage AI to analyze and synthesize diverse trending design elements, enabling the rapid prototyping of novel and highly diversified garment styles. This paradigm not only enhances creative exploration but also accelerates innovation in AI-augmented fashion design. In this work, we focus on intelligent fashion design and introduce VogFashion, an AI-powered system designed to enhance the creativity of fashion designers. VogFashion supports various design scenarios, including text-to-image generation, style extension, line drawing to fashion image conversion, and image fusion. By leveraging the Qwen Large Language Model (LLM) and our proposed metacognition-based human–AI collaborative regulation mechanism, the system empowers designers to efficiently generate desired visual outputs. Furthermore, VogFashion offers excellent scalability, allowing users to freely configure and integrate external Application Programming Interfaces (APIs). We believe that VogFashion will effectively support fashion designers in their creative design by enabling users to take the initiative in controlling the AI.

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Publication Details

Journal
SoftwareX
Published
2026-04-27
DOI
https://doi.org/10.1016/j.softx.2026.102661
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

VogFashion: an AI-driven intelligent system for fashion design

Xuechen Guo, Bangchao Wang, Zhengli Liu, Zhan Zheng et al.
SoftwareX
Generative Adversarial Networks and Image Synthesis
article

VogFashion: an AI-driven intelligent system for fashion design

Xuechen Guo, Bangchao Wang, Zhengli Liu, Zhan Zheng, Yanran Liu, Chen Gao, Kehan Chen
article en

Abstract

Artificial Intelligence (AI) technologies have demonstrated significant potential in fashion design. Designers can leverage AI to analyze and synthesize diverse trending design elements, enabling the rapid prototyping of novel and highly diversified garment styles. This paradigm not only enhances creative exploration but also accelerates innovation in AI-augmented fashion design. In this work, we focus on intelligent fashion design and introduce VogFashion, an AI-powered system designed to enhance the creativity of fashion designers. VogFashion supports various design scenarios, including text-to-image generation, style extension, line drawing to fashion image conversion, and image fusion. By leveraging the Qwen Large Language Model (LLM) and our proposed metacognition-based human–AI collaborative regulation mechanism, the system empowers designers to efficiently generate desired visual outputs. Furthermore, VogFashion offers excellent scalability, allowing users to freely configure and integrate external Application Programming Interfaces (APIs). We believe that VogFashion will effectively support fashion designers in their creative design by enabling users to take the initiative in controlling the AI.

SoftwareXVol. 34
Wuhan Textile University (CN)
Openalex Percentile: Top 10%
Generative Adversarial Networks and Image Synthesis
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