# NVlabs/stylegan3

Official PyTorch implementation of StyleGAN3

Repository: https://github.com/NVlabs/stylegan3
Canonical: https://ross.abutalabs.com/products/stylegan3
Language: Python
License: NOASSERTION
License Family: other
Last push: 2023-09-12T17:04:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1791, "days_push": 1086, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6943, forks 1238 (observed 2026-08-28T04:09:51.648990+00:00)

## What it is
Official PyTorch implementation of StyleGAN3 (Alias-Free GANs), a state-of-the-art generative adversarial network for high-fidelity image synthesis with translation- and rotation-equivariant generators. It includes training, visualization, video generation, and equivariance evaluation tools.

## Use cases
- generate photorealistic synthetic images with a GAN
- train a StyleGAN3 model on my own image dataset
- create interpolation videos from a trained GAN model
- analyze aliasing and spectral properties of a generator
- evaluate GAN equivariance to translation and rotation
- load and run pretrained StyleGAN2 pickles

## When to choose
- you need high-quality image synthesis with equivariant, alias-free generators
- you want to train or fine-tune StyleGAN2/3 models on custom datasets
- you need official, research-grade GAN tooling with visualization and metrics

## When to avoid
- you need a lightweight or CPU-only image generator
- you want diffusion models instead of GANs
- you lack a modern NVIDIA GPU, since training requires substantial CUDA resources

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, gpu-computing
- domain: deep-learning, computer-vision, image-processing, artificial-intelligence
- platform: python, cli
- tags: gan, stylegan, generative-models, pytorch, image-synthesis, nvidia-research, neurips-2021, gpu, linux

## Member repositories
- NVlabs/stylegan3 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:51.648990+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:41:13.759471+00:00, confidence not recorded.
  - readme: https://github.com/NVlabs/stylegan3 (fetched 2026-08-28T04:09:51.648990+00:00, sha 9394cdc16c92)
- Data as of 2026-08-30T08:39:29.467469+00:00.