Unsupervised Projection Networks for Generative Adversarial Networks
arXiv:1910.00579
Abstract
We propose the use of unsupervised learning to train projection networks that project onto the latent space of an already trained generator. We apply our method to a trained StyleGAN, and use our projection network to perform image super-resolution and clustering of images into semantically identifiable groups.
6 Pages, 8 Figures, ICCV 2019 Workshop: Sensing, Understanding and Synthesizing Humans