GANSpace: Discovering Interpretable GAN Controls

Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen +1

This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis, such as change of viewpoint, aging,…