harskish/ganspace

Health v2 · maintenance only

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1794 stars · 263 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

GANSpace is a research codebase implementing the NeurIPS 2020 paper on discovering interpretable controls for GANs via PCA in activation space. It includes modified BigGAN, StyleGAN, and StyleGAN2 models with interactive exploration and visualization tools for latent edit directions.

Use cases

• discover interpretable latent directions in a GAN
• edit generated images by changing viewpoint, lighting, or age
• explore StyleGAN2 latent space interactively
• visualize principal components of a GAN's latent space
• apply layer-wise edits to BigGAN in a StyleGAN-like manner
• create videos of GAN component traversals

When to choose

• you want to analyze or interpret controls of pretrained GANs like StyleGAN2 or BigGAN
• you need a research reference implementation of PCA-based latent space editing
• you want interactive exploration of GAN latent directions

When to avoid

• you need production image generation rather than research tooling
• you want to train GANs from scratch
• you need actively maintained code with recent dependency support
• you work outside PyTorch or lack a GPU

Facets

library · maturity maintenance

machine-learning deep-learning image-processing data-visualization deep-learning computer-vision image-processing artificial-intelligence python gan stylegan biggan pca latent-space-exploration neurips-2020 pytorch research-code image-synthesis linux macos gpu

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