Boosting GUI Prototyping with Diffusion Models
arXiv:2306.06233 · doi:10.1109/RE57278.2023.00035
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.
Accepted for The 31st IEEE International Requirements Engineering Conference 2023, RE@Next! track
References in corpus (5)
- Hierarchical Text-Conditional Image Generation with CLIP Latents
- Diffusion Models Beat GANs on Image Synthesis
- Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
- Wireframe-Based UI Design Search Through Image Autoencoder
- Screen2Vec: Semantic Embedding of GUI Screens and GUI Components