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We 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.
Pierre Dillenbourg, Richard Lee Davis, Kevin Gonyop Kim, Thiemo Wambsganss, Wei Jiang