# podgorskiy/ALAE

[CVPR2020] Adversarial Latent Autoencoders

Repository: https://github.com/podgorskiy/ALAE
Canonical: https://ross.abutalabs.com/products/alae
Language: Python
License Family: other
Topics: generative-adversarial-network, deep-learning, autoencoder, ffhq, celeba, celeba-hq, stylegan, alae, neural-network, generative-model, gan, face-generation, pytorch, pytorch-implementation, python, paper, paper-implementations, cvpr2020, computer-vision, machine-learning
Last push: 2021-01-23T04:24:54+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2731, "days_push": 2048, "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 3511, forks 544 (observed 2026-08-28T04:08:07.722499+00:00)

## What it is
Official PyTorch implementation of Adversarial Latent Autoencoders (ALAE/StyleALAE), a CVPR 2020 paper combining autoencoders with GAN training. It can generate 1024x1024 face images comparable to StyleGAN and perform reconstruction and manipulation of real face images.

## Use cases
- generate high-resolution face images
- reconstruct real face images from photos
- style mixing and latent manipulation of faces
- reproduce ALAE paper results
- train GAN-based autoencoders on FFHQ or CelebA-HQ
- learn disentangled latent representations

## When to choose
- you need StyleGAN-quality face generation plus real-image reconstruction
- you want to reproduce or build on the CVPR 2020 ALAE paper
- you need an autoencoder with GAN-level generative power in PyTorch

## When to avoid
- you need a maintained, actively updated codebase
- you need a license for commercial use (no explicit license file)
- your task is not face/generative image modeling

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, machine-learning, image-processing, computer-vision
- domain: deep-learning, computer-vision, image-processing, machine-learning
- platform: python
- tags: gan, autoencoder, stylegan, face-generation, paper-implementation, pytorch, cvpr2020, generative-models, gpu, linux

## Member repositories
- podgorskiy/ALAE (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:07.722499+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 2026-08-29T18:35:43.542154+00:00, confidence not recorded.
  - readme: https://github.com/podgorskiy/ALAE (fetched 2026-08-28T04:08:07.722499+00:00, sha acd4c19dbf9a)
- Data as of 2026-08-30T08:39:29.467469+00:00.