GUIGAN: learning to generate GUI designs using generative adversarial networks

Tianming Zhao, Chunyang Chen, Yuanning Liu, Xiaodong Zhu

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

Graphical User Interface (GUI) is ubiquitous in almost all modern desktop software, mobile applications and online websites. A good GUI design is crucial to the success of the software in the market, but designing a good GUI which requires much innovation and creativity is difficult even to well-trained designers. In addition, the requirement of rapid development of GUI design also aggravates designers' working load. So, the availability of various automated generated GUIs can help enhance the design personalization and specialization as they can cater to the taste of different designers. To assist designers, we develop a model tool to automatically generate GUI designs. Different from conventional image generation models based on image pixels, our tool is to reuse GUI components collected from existing mobile app GUIs for composing a new design which is similar to natural-language generation. Our tool is based on SeqGAN by modelling the GUI component style compatibility and GUI structure. The evaluation demonstrates that our model significantly outperforms the best of the baseline methods by 30.77% in Fr'echet Inception distance (FID) and 12.35% in 1-Nearest Neighbor Accuracy (1-NNA). Through a pilot user study, we provide initial evidence of the usefulness of our approach for generating acceptable brand new GUI designs.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/ACM 43rd International Conference on Software Engineering, ICSE 2021
EditorsArie van Deursen, Tao Xie
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages748-760
Number of pages13
ISBN (Electronic)9780738113197
ISBN (Print)9781665402965
DOIs
Publication statusPublished - 2021
EventInternational Conference on Software Engineering 2021 - Online, Madrid, Spain
Duration: 25 May 202128 May 2021
Conference number: 43rd
https://conf.researchr.org/committee/icse-2021/icse-2021-organizing-committe
https://conf.researchr.org/home/icse-2021
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9401806/proceeding (Proceedings)

Publication series

NameProceedings - International Conference on Software Engineering
PublisherThe Institute of Electrical and Electronics Engineers, Inc.
ISSN (Print)0270-5257
ISSN (Electronic)1558-1225

Conference

ConferenceInternational Conference on Software Engineering 2021
Abbreviated titleICSE 2021
Country/TerritorySpain
CityMadrid
Period25/05/2128/05/21
Internet address

Keywords

  • Deep learning
  • Generative Adversarial Network
  • Graphical User Interface
  • GUI design
  • Mobile application

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