genforce/interfacegan

Health v2 · maintenance only

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1561 stars · 278 forks observed · 2026-08-28

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

InterFaceGAN is a Python research library that interprets the latent space of pretrained GANs (PGGAN, StyleGAN) to find semantic subspaces for face editing. It provides pretrained attribute boundaries and scripts to manipulate facial attributes like age, gender, pose, and expression in generated faces.

Use cases

• edit facial attributes in GAN-generated faces
• control age or gender in StyleGAN outputs
• interpret latent space of generative adversarial networks
• fix artifacts in GAN-synthesized images
• reproduce CVPR 2020 semantic face editing research
• change pose or expression in generated portraits

When to choose

• you need latent-space semantic editing of faces with PGGAN or StyleGAN
• you are researching GAN interpretability and disentangled representations
• you want pretrained attribute boundaries for face manipulation

When to avoid

• you need editing of non-face images or modern GANs beyond PGGAN/StyleGAN
• you need a production-ready image editing application
• you require active maintenance or recent framework compatibility

Facets

library · maturity maintenance

machine-learning deep-learning image-processing data-science deep-learning computer-vision image-processing artificial-intelligence python windows gan latent-space face-editing stylegan pggan pytorch research cvpr-2020 generative-models linux macos

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