Investigating Semantically-enhanced Exploration of GAN Latent Space via a Digital Mood Board
Published in Extended Abstracts of ACM CHI Conference on Human Factors in Computing Systems, 2023
Qian Wan, and Zhicong Lu
During past decades, Artificial Intelligence (AI) has been consistently used in Creativity Support Tools (CSTs). Recently, with the development of generative AI models, particularly Generative Adversarial Nets (GAN) in Computer Vision, it became possible that AI directly generates visual ideas. However, there were rarely any work in creativity research that harnessed the design ideas generated by such models directly for design space exploration. To that end we designed a digital mood board as a technology probe to support semantically-enhanced exploration of the StyleGAN latent space. We compared the mood board with traditional gallery display. Preliminary results showed that such design offered a more enjoyable and explicit way of exploring AI generated visual ideas, but gallery display was found to be more straightforward and less demanding.