# Resolution Dependant GAN Interpolation for Controllable Image Synthesis Between Domains

**Authors:** Justin N. M. Pinkney, Doron Adler  
**arXiv:** [2010.05334](https://arxiv.org/abs/2010.05334)  
**Date:** 2020-10-11  
**Summary page:** https://www.summarizepaper.com/fr/paper/2010.05334v1/

## Abstract

GANs can generate photo-realistic images from the domain of their training data. However, those wanting to use them for creative purposes often want to generate imagery from a truly novel domain, a task which GANs are inherently unable to do. It is also desirable to have a level of control so that there is a degree of artistic direction rather than purely curation of random results. Here we present a method for interpolating between generative models of the StyleGAN architecture in a resolution dependant manner. This allows us to generate images from an entirely novel domain and do this with a degree of control over the nature of the output.