Boosting GUI Prototyping with Diffusion Models

• URL: http://arxiv.org/abs/2306.06233v1
• Date: Fri, 9 Jun 2023 20:08:46 GMT
• Title: Boosting GUI Prototyping with Diffusion Models
• Authors: Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais, Binbin Xu, Pierre Louis Bernard, G\'erard Dray
• Abstract summary: Deep learning models such as Stable Diffusion have emerged as a powerful text-to-image tool. We propose UI-Diffuser, an approach that leverages Stable Diffusion to generate mobile UIs. Preliminary results show that UI-Diffuser provides an efficient and cost-effective way to generate mobile GUI designs.
• Score: 0.440401067183266
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: GUI (graphical user interface) prototyping is a widely-used technique in requirements engineering for gathering and refining requirements, reducing development risks and increasing stakeholder engagement. However, GUI prototyping can be a time-consuming and costly process. In recent years, deep learning models such as Stable Diffusion have emerged as a powerful text-to-image tool capable of generating detailed images based on text prompts. In this paper, we propose UI-Diffuser, an approach that leverages Stable Diffusion to generate mobile UIs through simple textual descriptions and UI components. Preliminary results show that UI-Diffuser provides an efficient and cost-effective way to generate mobile GUI designs while reducing the need for extensive prototyping efforts. This approach has the potential to significantly improve the speed and efficiency of GUI prototyping in requirements engineering.

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