StyleGAN

NVIDIA

Structures found in this family (5)

Intrinsic-dimension profile across depth, Linear Direction, Affine Subspace, Linear Subspace, Curvature profile of the representation manifold

By model (3)

StyleGAN2 (trained on FFHQ, 1024x1024)

Intrinsic-dimension profile across depth, Linear Direction, Affine Subspace, Linear Subspace

StyleGAN (trained on FFHQ, 1024x1024)

Linear Direction

StyleGAN2 (Face256, trained on FFHQ)

Curvature profile of the representation manifold

Observations (5)

Local intrinsic dimension of a real StyleGAN2 latent manifold varies across latent space and correlates with disentanglement

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

InterFaceGAN SVM boundary normals are linear, editable, and partially entangled

StyleGAN2's W space is globally warped; local bases avoid traversal collapse

Image variation in several real pretrained GANs concentrates along surprisingly few, position-homogeneous major axes of the pullback metric

Papers

Analyzing the Latent Space of GAN through Local Dimension Estimation (2023), GANSpace: Discovering Interpretable GAN Controls (2020), InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs (2020), Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs (2021), The Geometry of Deep Generative Image Models and its Applications (2021)