WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

Authors official PyTorch implementation of the WarpedGANSpace: Finding non-linear RBF paths in GAN latent space (ICCV 2021). If you use this code for your research, please cite our paper.

Overview

In this work, we try to discover non-linear interpretable paths in GAN latent space. For doing so, we model non-linear paths using RBF-based warping functions, which by warping the latent space, endow it with vector fields (their gradients). We use the latter to traverse the latent space across the paths determined by the aforementioned vector fields for any given latent code.

Each warping function is defined by a set of N support vectors (a “support set”) and its gradient is given analytically as shown above. For a given warping function f^k

 

 

 

To finish reading, please visit source site