mlsanityData to 7 Oct 2026

Kindling the Darkness: A Practical Low-light Image Enhancer

arXiv 1905.04161 ↗First posted 4 May 2019cs.CVcited by 355

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Cited by 30 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Images captured under low-light conditions often suffer from (partially) poor visibility. Besides unsatisfactory lightings, multiple types of degradations, such as noise and color distortion due to the limited quality of cameras, hide in the dark. In other words, solely turning up the brightness of dark regions will inevitably amplify hidden artifacts. This work builds a simple yet effective network for Kindling the Darkness (denoted as KinD), which, inspired by Retinex theory, decomposes images into two components. One component (illumination) is responsible for light adjustment, while the other (reflectance) for degradation removal. In such a way, the original space is decoupled into two smaller subspaces, expecting to be better regularized/learned. It is worth to note that our network is trained with paired images shot under different exposure conditions, instead of using any ground-truth reflectance and illumination information. Extensive experiments are conducted to demonstrate the efficacy of our design and its superiority over state-of-the-art alternatives. Our KinD is robust against severe visual defects, and user-friendly to arbitrarily adjust light levels. In addition, our model spends less than 50ms to process an image in VGA resolution on a 2080Ti GPU. All the above merits make our KinD attractive for practical use.

Key facts. Cited by 355 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2019.

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Citing papers per year: 2021: 36; 2022: 47; 2023: 79; 2024: 72; 2025: 69; 2026: 52.

355 papers.

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  1. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 301
  2. 2023Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancementcited by 228
  3. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancementcited by 198
  4. 2021Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimationcited by 192
  5. 2021Low-Light Image Enhancement with Normalizing Flowcited by 184
  6. 2022Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Methodcited by 174
  7. 2022Learning Enriched Features for Fast Image Restoration and Enhancementcited by 150
  8. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  9. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 139
  10. 2023Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Modelcited by 118
  11. 2023Iterative Prompt Learning for Unsupervised Backlit Image Enhancementcited by 107
  12. 2021R2RNet: Low-light Image Enhancement via Real-low to Real-normal Networkcited by 106
38 more
  1. 2022ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removalcited by 102
  2. 2022LEDNet: Joint Low-light Enhancement and Deblurring in the Darkcited by 95
  3. 2023Implicit Neural Representation for Cooperative Low-light Image Enhancementcited by 92
  4. 2023Global Structure-Aware Diffusion Process for Low-Light Image Enhancementcited by 92
  5. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
  6. 2022You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correctioncited by 81
  7. 2023Low-Light Image Enhancement via Structure Modeling and Guidancecited by 78
  8. 2022Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppressioncited by 73
  9. 2022AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancementcited by 70
  10. 2023Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Modelcited by 69
  11. 2023Residual Denoising Diffusion Modelscited by 68
  12. 2023Pyramid Diffusion Models For Low-light Image Enhancementcited by 67
  13. 2021Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tablescited by 65
  14. 2021Low-light Image Enhancement via Breaking Down the Darknesscited by 65
  15. 2023FourLLIE: Boosting Low-Light Image Enhancement by Fourier Frequency Informationcited by 64
  16. 2021Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancementcited by 60
  17. 2022Multitask AET with Orthogonal Tangent Regularity for Dark Object Detectioncited by 59
  18. 2024Retinexmamba: Retinex-based Mamba for Low-light Image Enhancementcited by 59
  19. 2024Zero-Reference Low-Light Enhancement via Physical Quadruple Priorscited by 58
  20. 2021Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Darkcited by 57
  21. 2023Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancementcited by 57
  22. 2024FreqMamba: Viewing Mamba from a Frequency Perspective for Image Derainingcited by 57
  23. 2022SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancementcited by 50
  24. 2024Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approachcited by 48
  25. 2024MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Spacecited by 48
  26. 2022Abandoning the Bayer-Filter to See in the Darkcited by 40
  27. 2023Lighting up NeRF via Unsupervised Decomposition and Enhancementcited by 40
  28. 2023Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Networkcited by 33
  29. 2024GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrievalcited by 33
  30. 2021StarEnhancer: Learning Real-Time and Style-Aware Image Enhancementcited by 32
  31. 2023Underwater Image Enhancement by Transformer-based Diffusion Model with Non-uniform Sampling for Skip Strategycited by 32
  32. 2021Semantically Contrastive Learning for Low-light Image Enhancementcited by 31
  33. 2023CLE Diffusion: Controllable Light Enhancement Diffusion Modelcited by 30
  34. 2021HLA-Face: Joint High-Low Adaptation for Low Light Face Detectioncited by 28
  35. 2025Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restorationcited by 27
  36. 2021ReLLIE: Deep Reinforcement Learning for Customized Low-Light Image Enhancementcited by 26
  37. 2021Towards Low Light Enhancement with RAW Imagescited by 26
  38. 2021DarkLighter: Light Up the Darkness for UAV Trackingcited by 24

50 most cited of 355 All 355 (JSON)