GANSpace PCA finds near-independent, unimodal, content-style-separated directions

Harkonen et al. find interpretable GAN edit directions entirely unsupervised via PCA on StyleGAN/StyleGAN2 W space and a BigGAN feature tensor [harkonen-etal-2020-ganspace] For BigGAN, which lacks a learned intermediate latent, PCA components are transferred back to the z latent via linear regression [harkonen-etal-2020-ganspace] The StyleGAN2 latent's PCA coordinates are nearly Gaussian/unimodal (entropies 6.9-8.7 bits) and nearly independent (pairwise mutual information 0-0.3 bits) [harkonen-etal-2020-ganspace] The first ~20 principal components control large geometric/viewpoint changes, with the first 100 of 512 dims capturing 85% of variance [harkonen-etal-2020-ganspace] Layer-wise restriction of a PCA direction cleanly separates content from style (e.g. pure head rotation at layers 0-2), an effect absent for random directions [harkonen-etal-2020-ganspace]