mlsanityData to 14 Oct 2026

CLE Diffusion: Controllable Light Enhancement Diffusion Model

arXiv 2308.06725 ↗First posted 13 Aug 2023cs.CV cs.AI cs.MMcited by 30

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

Low light enhancement has gained increasing importance with the rapid development of visual creation and editing. However, most existing enhancement algorithms are designed to homogeneously increase the brightness of images to a pre-defined extent, limiting the user experience. To address this issue, we propose Controllable Light Enhancement Diffusion Model, dubbed CLE Diffusion, a novel diffusion framework to provide users with rich controllability. Built with a conditional diffusion model, we introduce an illumination embedding to let users control their desired brightness level. Additionally, we incorporate the Segment-Anything Model (SAM) to enable user-friendly region controllability, where users can click on objects to specify the regions they wish to enhance. Extensive experiments demonstrate that CLE Diffusion achieves competitive performance regarding quantitative metrics, qualitative results, and versatile controllability. Project page: https://yuyangyin.github.io/CLEDiffusion/

Key facts. Cited by 30 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 45 of its 75 references that are in the map. First posted on arXiv 13 Aug 2023.

Builds on

45 of 75 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023Monocular Depth Estimation using Diffusion Models28 Feb
  2. 2022NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360deg Views29 Nov
  3. 2022Novel View Synthesis with Diffusion Models6 Oct
  4. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep

Other references · 41

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  5. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  6. 2020Denoising Diffusion Implicit Modelscited by 9,781
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  8. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  9. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  10. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  11. 2022Classifier-Free Diffusion Guidancecited by 5,847
  12. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
29 more
  1. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
  2. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
  3. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,333
  4. 2017Improved Training of Wasserstein GANscited by 2,235
  5. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  6. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  7. 2021Variational Diffusion Modelscited by 1,153
  8. 2021Resolution-robust Large Mask Inpainting with Fourier Convolutionscited by 738
  9. 2018Deep Retinex Decomposition for Low-Light Enhancementcited by 723
  10. 2021Score-based Generative Modeling in Latent Spacecited by 636
  11. 2020Zero-Reference Deep Curve Estimation for Low-Light Image Enhancementcited by 542
  12. 2019EnlightenGAN: Deep Light Enhancement without Paired Supervisioncited by 466
  13. 2019Kindling the Darkness: A Practical Low-light Image Enhancercited by 355
  14. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354
  15. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 302
  16. 2021Deblurring via Stochastic Refinementcited by 249
  17. 2015LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancementcited by 224
  18. 2022Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Modelscited by 215
  19. 2016Unrolled Generative Adversarial Networkscited by 208
  20. 2023Text-To-4D Dynamic Scene Generationcited by 205
  21. 2021Low-Light Image Enhancement with Normalizing Flowcited by 185
  22. 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusioncited by 180
  23. 2019Classification Accuracy Score for Conditional Generative Modelscited by 136
  24. 2022MatteFormer: Transformer-Based Image Matting via Prior-Tokenscited by 48
  25. 2017MSR-net:Low-light Image Enhancement Using Deep Convolutional Networkcited by 43
  26. 2020Towards Unsupervised Deep Image Enhancement with Generative Adversarial Networkcited by 38
  27. 2018Joint Enhancement and Denoising Method via Sequential Decompositioncited by 32
  28. 2022Half Wavelet Attention on M-Net+ for Low-Light Image Enhancementcited by 20
  29. 2021CERL: A Unified Optimization Framework for Light Enhancement with Realistic Noisecited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 13; 2025: 10; 2026: 5.

30 papers.

Sort:

By area:

  1. 2024C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detectioncited by 113
  2. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 109
  3. 2024Diffusion Models in Low-Level Vision: A Surveycited by 74
  4. 2024ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidancecited by 18
  5. 2024AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancementcited by 16
  6. 2024DiffRetouch: Using Diffusion to Retouch on the Shoulder of Expertscited by 14
  7. 2024Efficient Diffusion as Low Light Enhancercited by 13
  8. 2024LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusioncited by 12
  9. 2024LoLI-Street: Benchmarking Low-Light Image Enhancement and Beyondcited by 10
  10. 2025TSCnet: A Text-driven Semantic-level Controllable Framework for Customized Low-Light Image Enhancementcited by 9
  11. 2023JoReS-Diff: Joint Retinex and Semantic Priors in Diffusion Model for Low-light Image Enhancementcited by 8
  12. 2024EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopycited by 8
18 more
  1. 2024Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Modelcited by 8
  2. 2025PromptLNet: Region-Adaptive Aesthetic Enhancement via Prompt Guidance in Low-Light Enhancement Netcited by 8
  3. 2025PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusioncited by 7
  4. 2024Benchmarking Segmentation Models with Mask-Preserved Attribute Editingcited by 6
  5. 2024A Comprehensive Survey on Diffusion Models and Their Applicationscited by 4
  6. 2025Structure-guided Diffusion Transformer for Low-Light Image Enhancementcited by 4
  7. 2025UDBE: Unsupervised Diffusion-based Brightness Enhancement in Underwater Imagescited by 3
  8. 2025Advances in Artificial Intelligence: A Review for the Creative Industriescited by 2
  9. 2026Benchmarking Semantic Segmentation Models via Appearance and Geometry Attribute Editingcited by 2
  10. 2026Towards Controllable Low-Light Image Enhancement: A Continuous Multi-illumination Dataset and Efficient State Space Frameworkcited by 1
  11. 2026ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancementcited by 1
  12. 2024Technique Report of CVPR 2024 PBDL Challengescited by 0
  13. 2025Unpaired Object-Level SAR-to-Optical Image Translation for Aircraft with Keypoints-Guided Diffusion Modelscited by 0
  14. 2025Uncertainty-Aware Spatial Color Correlation for Low-Light Image Enhancementcited by 0
  15. 2025Diffusion Models for Low-Light Image Enhancement: A Multi-Perspective Taxonomy and Performance Analysiscited by 0
  16. 2025Consist-Retinex: One-Step Noise-Emphasized Consistency Training Accelerates High-Quality Retinex Enhancementcited by 0
  17. 2026Diffusion-Based Low-Light Image Enhancement with Color and Luminance Priorscited by 0
  18. 2026P-PatchDiff: Progressive Patch Diffusion Models for Low-light Image Enhancementcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025LightLab: Controlling Light Sources in Images with Diffusion Models
  2. 2026Learning Illumination Control in Diffusion Models
  3. 2025PractiLight: Practical Light Control Using Foundational Diffusion Models
  4. 2024DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generation
  5. 2023Global Structure-Aware Diffusion Process for Low-Light Image Enhancement
  6. 2025Boosting Fidelity for Pre-Trained-Diffusion-Based Low-Light Image Enhancement via Condition Refinement
  7. 2024LightIt: Illumination Modeling and Control for Diffusion Models
  8. 2025TransLight: Image-Guided Customized Lighting Control with Generative Decoupling