VITA-Group/EnlightenGAN

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1091 stars · 209 forks observed · 2026-08-28

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

Official PyTorch implementation of EnlightenGAN, an IEEE TIP paper on deep low-light image enhancement without paired supervision using generative adversarial networks. It includes training and testing scripts, pretrained models, and unpaired training/testing datasets.

Use cases

• enhance low-light photos without paired training data
• brighten dark images with a GAN model
• train an unsupervised light enhancement network
• run inference on dark images with pretrained EnlightenGAN weights
• reproduce the EnlightenGAN paper results
• compare low-light enhancement on LIME, MEF, NPE, VV, DICP benchmarks

When to choose

• you need low-light image enhancement without paired supervision
• you want a research baseline or pretrained model for image relighting
• you have GPU resources and want to train or fine-tune a GAN-based enhancer

When to avoid

• you need a production-ready, actively maintained image enhancement library
• you lack multi-GPU hardware and cannot adjust batch sizes
• you need paired-supervision training or real-time mobile inference

Facets

library · maturity maintenance

image-processing deep-learning machine-learning image-processing computer-vision deep-learning python gan low-light-enhancement unsupervised-learning pytorch research-code ieee-tip gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="VITA-Group/EnlightenGAN")