Generative User Interface for the Mobile Apps: Image Synthesis with VAEs, GANs, and Stable Diffusion

Introduction of the neural network models in creating intelligent mobile user interfaces poses a new challenge for researchers and the application developers. Each year, using the generative models in automatic image generation becomes more and more important. Developing interfaces based on the element images and the entire screen is considered an innovation solution in design. The paper presents results of testing the Variational Autoencoder (VAE), Generative Adversarial Network (GAN) and Stable Diffusion models aimed at studying these approaches potential in creating the user interfaces. To compare the approaches, it analyzes the obtained images as the user interfaces based on the usability metrics. The analysis makes it possible to formulate recommendations for selecting suitable models for various applications and highlights the areas for further research.

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Published
2025-04-08
DOI
https://doi.org/10.1109/reepe63962.2025.10970899
Primary Topic
3D Modeling in Geospatial Applications
Type
article
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article

Generative User Interface for the Mobile Apps: Image Synthesis with VAEs, GANs, and Stable Diffusion

Dmitry A. Vidmanov, Konstantin V. Kostinich
3D Modeling in Geospatial Applications
article

Generative User Interface for the Mobile Apps: Image Synthesis with VAEs, GANs, and Stable Diffusion

Dmitry A. Vidmanov, Konstantin V. Kostinich
article en

Abstract

Introduction of the neural network models in creating intelligent mobile user interfaces poses a new challenge for researchers and the application developers. Each year, using the generative models in automatic image generation becomes more and more important. Developing interfaces based on the element images and the entire screen is considered an innovation solution in design. The paper presents results of testing the Variational Autoencoder (VAE), Generative Adversarial Network (GAN) and Stable Diffusion models aimed at studying these approaches potential in creating the user interfaces. To compare the approaches, it analyzes the obtained images as the user interfaces based on the usability metrics. The analysis makes it possible to formulate recommendations for selecting suitable models for various applications and highlights the areas for further research.

Bauman Moscow State Technical University (RU)
Openalex Percentile: Top 90%
3D Modeling in Geospatial Applications
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Generative User Interface for the Mobile Apps: Image Synthesis with VAEs, GANs, and Stable Diffusion — Dmitry A. Vidmanov, Konstantin V. Kostinich · (2025) | TGRS Research Map | TGRS