Boosting GUI Prototyping with Diffusion Models

TL;DR

This paper introduces UI-Diffuser, a novel method that uses Stable Diffusion to generate mobile GUI prototypes from text descriptions, aiming to make GUI prototyping faster and more cost-effective.

Contribution

The paper presents UI-Diffuser, the first approach leveraging diffusion models for automated GUI generation from textual prompts in requirements engineering.

Findings

UI-Diffuser generates detailed mobile UIs from text prompts.

Preliminary results show reduced prototyping time and costs.

The approach enhances efficiency in GUI design processes.

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.