資源帖- low-light image enhancement 論文程式碼資料集

sereasuesue發表於2020-12-05

Datasets

datasetbrief introductionlink
VIP-LowLightEight Natural Images Captured in Very Low-Light Conditionshttps://uwaterloo.ca/vision-image-processing-lab/research-demos/vip-lowlight-dataset
ReNOIRRENOIR - A Dataset for Real Low-Light Image Noise Reductionhttp://ani.stat.fsu.edu/~abarbu/Renoir.html
Raw Image Low-Light Object-https://wiki.qut.edu.au/display/cyphy/Datasets
SIDLearning to see in the dark;
light level (outdoor scene 0.2 lux - 5 lux; indoor scene: 0.03 lux - 0.3 lux)		http://vladlen.info/publications/learning-see-dark （including codes）
ExDARKGetting to Know Low-light Images with The Exclusively Dark Datasethttps://github.com/cs-chan/Exclusively-Dark-Image-Dataset （including codes）
MIT-Adobe FiveKLearning Photographic Global Tonal Adjustment with a Database of Input / Output Image Pairs
(with ~4% low light images)		https://data.csail.mit.edu/graphics/fivek
LRAICE-DatasetA Learning-to-Rank Approach for Image Color Enhancement-
The 500px DatasetExposure: A White-Box Photo Post-Processing Framework-
DPEDDSLR-quality photos on mobile devices with deep convolutional networkshttp://people.ee.ethz.ch/~ihnatova
LOLDeep Retinex Decomposition for Low-Light Enhancementhttps://daooshee.github.io/BMVC2018website
VV - most challenging casesBusting image enhancement and tone-mapping algorithms: A collection of the most challenging cases
from Vassilios Vonikakis		https://sites.google.com/site/vonikakis/datasets/challenging-dataset-for-enhancement
VV - PhosA color image database of 15 scenes captured under different illumination conditions
from Vassilios Vonikakis		http://robotics.pme.duth.gr/phos2.html
SICEA large-scale multi-exposure image dataset, which contains 589 elaborately selected high-resolution multi-exposure sequences with 4,413 imageshttps://github.com/csjcai/SICE
The Extended Yale Face Database BThe extended Yale Face Database B contains 16128 images of 28 human subjects under 9 poses and 64 illumination conditions.http://vision.ucsd.edu/~iskwak/ExtYaleDatabase/ExtYaleB.html
the nighttime image datasetA dataset which contains source images in bad visibility and their enhanced images processed by different enhancement algorithmshttp://mlg.idm.pku.edu.cn/

 

2020

  • Meng et al, GIA-Net: Global Information Aware Network for Low-light Imaging. [paper][code]
  • Kwon et al, DALE : Dark Region-Aware Low-light Image Enhancement. [paper][code]
  • Yang et al, From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement. [paper][code]
  • Atoum et al, Color-wise Attention Network for Low-light Image Enhancement. [paper][code]
  • Lv et al, Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset. [paper][code]
  • Guo et al, Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement. [paper][code]
  • Wei et al, A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising. [paper][code]
  • Fu et al, Learning an Adaptive Model for Extreme Low-light Raw Image Processing. [paper][code]
  • Wang et al, Extreme Low-Light Imaging with Multi-granulation Cooperative Networks. [paper][code]
  • Karadeniz et al, Burst Denoising of Dark Images. [paper][code]
  • Xiong et al, Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks. [paper][code]
  • Liang et al, Deep Bilateral Retinex for Low-Light Image Enhancement. [paper][code]
  • Zhang et al, ATTENTION-BASED NETWORK FOR LOW-LIGHT IMAGE ENHANCEMENT. [paper][code]
  • Li et al, Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement. [paper][code]
  • Zhang et al, Self-supervised Image Enhancement Network: Training with Low Light Images Only. [paper][code]
  • Xu et al, Learning to Restore Low-Light Images via Decomposition-and-Enhancement. [paper][code]

2019

  • Wang et al, Underexposed Photo Enhancement using Deep Illumination Estimation. [paper][code]
  • Loh et al, Low-light image enhancement using Gaussian Process for features retrieval. [paper][code]
  • Zhang et al, Kindling the Darkness: A Practical Low-light Image Enhancer. [paper][code]
  • Ren et al, Low-Light Image Enhancement via a Deep Hybrid Network. [paper][code]
  • Jiang et al, EnlightenGAN: Deep Light Enhancement without Paired Supervision. [paper][code]
  • Wang et al, RDGAN: RETINEX DECOMPOSITION BASED ADVERSARIAL LEARNING FOR LOW-LIGHT ENHANCEMENT. [paper][code]

2018

  • Chen et al, Learning to See in the Dark. [paper][code]
  • Wei et al, Deep Retinex Decomposition for Low-Light Enhancement. [paper][code]
  • Wang et al, GLADNet: Low-Light Enhancement Network with Global Awareness. [paper][code]
  • Lv et al, MBLLEN: Low-light Image/Video Enhancement Using CNNs. [paper][code]
  • Jiang et al, Deep Refinement Network for Natural Low-Light Image Enhancement in Symmetric Pathways. [paper][code]
  • Cai et al, Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images. [paper][code]

2017

  • GHARBI et al, Deep Bilateral Learning for Real-Time Image Enhancement. [paper][code]
  • Shen et al, MSR-net:Low-light Image Enhancement Using Deep Convolutional Network. [paper][code]
  • Tao et al, LLCNN: A convolutional neural network for low-light image enhancement. [paper][code]
  • Ying et al, A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement. [paper][code]

2016

  • Lore et al, LLNet: A Deep Autoencoder approach to Natural Low-light Image Enhancement. [paper][code]
  • Guo et al, LIME: Low-Light Image Enhancement via Illumination Map Estimation. [paper][code]

3 Image Quality Assessment Metrics

 連結見cxtalk/You-Can-See-Clearly-Now: A collection of awesome low-light image enhancement methods. (github.com)

參考連結：dawnlh/low-light-image-enhancement-resources: This is a resouce list for low light image enhancement (github.com)

 

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