Jiang, WeiDavis, Richard LeeKim, Kevin GonyopDillenbourg, Pierre2022-08-212022-08-212022-08-212022-07-20https://infoscience.epfl.ch/handle/20.500.14299/190194We have developed a new tool that makes it possible for people with zero programming experience to intentionally and meaningfully explore the latent space of a GAN. We combine a number of methods from the literature into a single system that includes multiple functionalities: uploading and locating images in the latent space, image generation with text, visual style mixing, and intentional and intuitive latent space exploration. This tool was developed to provide a means for designers to explore the "design space" of their domains. Our goal was to create a system to support novices in gaining a more complete, expert understanding of their domain's design space by lowering the barrier of entry to using deep generative models in creative practice.Generative Adversarial NetworksCreativity Support ToolsDesign Space Explorationtext::conference output::conference proceedings::conference paper