GANSpiration: Balancing Targeted and Serendipitous Inspiration in User Interface Design with ...

GANSpiration: Balancing Targeted and Serendipitous Inspiration in User Interface Design with Style-Based Generative Adversarial Network
Mohammad Amin Mozaffari, Xinyuan Zhang, Jinghui Cheng, Jin L.C. Guo

CHI'22: ACM Conference on Human Factors in Computing Systems
Session: Interacting with Smart Technology

Abstract
Inspiration from design examples plays a crucial role in the creative process of user interface design. However, the current inspiration-support tools and techniques usually only focus on example browsing with limited control or similarity-based example retrieval, leading to undesirable design outcomes such as focus drift or design fixation. To address these issues, we propose the GANSpiration approach that leverages a style-based Generative Adversarial Network to suggest design examples for both targeted and serendipitous inspiration. A quantitative evaluation revealed that the outputs of GANSpiration-based example suggestion approaches are relevant to the input design, and at the same time include diverse instances. A user study with professional UI/UX practitioners showed that the examples suggested by GANSpiration are viable sources of inspiration for overall design concepts and specific design elements. GANSpiration paves the road of using advanced generative machine learning techniques in supporting the creative design practice.

WEB:: https://chi2022.acm.org/

Pre-recorded presentations of CHI 2022