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JIA-Lab-research/SNR-Aware-Low-Light-Enhance

This is the official implementation for the paper "SNR-aware low-light image enhancement" in CVPR2022 observed · 2026-08-28

github.com/JIA-Lab-research/SNR-Aware-Low-Light-Enhance · Python observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1628
  • days_rel: n/a
  • days_push: 1381
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1037 stars · 108 forks observed · 2026-08-28

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

Official PyTorch implementation of the CVPR 2022 paper 'SNR-aware Low-Light Image Enhancement'. It combines SNR-aware transformers and convolutional models to enhance low-light images with spatial-varying operations guided by a signal-to-noise-ratio prior.

Use cases

  • enhance dark low-light photos
  • brighten images taken in low light
  • denoise and enhance low-SNR image regions
  • train a low-light enhancement model on the LOL dataset
  • reproduce CVPR 2022 low-light enhancement results
  • evaluate low-light enhancement on SID, SMID, and SDSD datasets

When to choose

  • you need state-of-the-art low-light image enhancement with SNR-aware modeling
  • you want a research-grade PyTorch codebase for the CVPR 2022 paper
  • you are benchmarking on LOL, SID, SMID, or SDSD low-light datasets

When to avoid

  • you need a production-ready image enhancement service with support and license guarantees
  • you want a simple one-line API without GPU or dataset setup
  • you need enhancement of non-photographic or synthetic graphics

Facets

library · maturity maintenance

image-processing deep-learning machine-learning computer-vision image-processing deep-learning artificial-intelligence python windows low-light-enhancement snr-aware cvpr2022 pytorch image-restoration research-code transformers linux macos gpu

1 source

Member repositories

RepositoryRoleHealth v2
JIA-Lab-research/SNR-Aware-Low-Light-Enhancemain32

For agents

markdown · JSON · MCP: product_card(name="JIA-Lab-research/SNR-Aware-Low-Light-Enhance")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem