  Inspiration from design examples plays a crucial role in the creative process
of user interface design. However, current tools and techniques that support
inspiration usually only focus on example browsing with limited user control or
similarity-based example retrieval, leading to undesirable design outcomes such
as focus drift and design fixation. To address these issues, we propose the
GANSpiration approach that suggests design examples for both targeted and
serendipitous inspiration, leveraging a style-based Generative Adversarial
Network. 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 our
approach serve as viable sources of inspiration for overall design concepts and
specific design elements. Overall, our work paves the road of using advanced
generative machine learning techniques in supporting the creative design
practice.
