mlsanityData to 7 Oct 2026

NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images

arXiv 2005.03560 ↗First posted 7 May 2020cs.CVcited by 108

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Abstract (arXiv)

Image dehazing is an ill-posed problem that has been extensively studied in the recent years. The objective performance evaluation of the dehazing methods is one of the major obstacles due to the lacking of a reference dataset. While the synthetic datasets have shown important limitations, the few realistic datasets introduced recently assume homogeneous haze over the entire scene. Since in many real cases haze is not uniformly distributed we introduce NH-HAZE, a non-homogeneous realistic dataset with pairs of real hazy and corresponding haze-free images. This is the first non-homogeneous image dehazing dataset and contains 55 outdoor scenes. The non-homogeneous haze has been introduced in the scene using a professional haze generator that imitates the real conditions of hazy scenes. Additionally, this work presents an objective assessment of several state-of-the-art single image dehazing methods that were evaluated using NH-HAZE dataset.

Key facts. Cited by 108 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 May 2020.

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Citing papers per year: 2021: 8; 2022: 7; 2023: 13; 2024: 27; 2025: 29; 2026: 24.

108 papers.

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  1. 2022Vision Transformers for Single Image Dehazingcited by 255
  2. 2021Contrastive Learning for Compact Single Image Dehazingcited by 219
  3. 2023Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Modelscited by 86
  4. 2023ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restorationcited by 77
  5. 2023RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priorscited by 73
  6. 2024FreqMamba: Viewing Mamba from a Frequency Perspective for Image Derainingcited by 57
  7. 2022Not Just Streaks: Towards Ground Truth for Single Image Derainingcited by 31
  8. 2024PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructionscited by 31
  9. 2022Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removalcited by 28
  10. 2025Visual-Instructed Degradation Diffusion for All-in-One Image Restorationcited by 26
  11. 2025Learning Hazing to Dehazing: Towards Realistic Haze Generation for Real-World Image Dehazingcited by 23
  12. 2023Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Priorcited by 22
38 more
  1. 2025Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Datacited by 21
  2. 2021A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learningcited by 19
  3. 2025Multi-Agent Image Restorationcited by 19
  4. 2023MixDehazeNet : Mix Structure Block For Image Dehazing Networkcited by 18
  5. 2023Mutual Information-driven Triple Interaction Network for Efficient Image Dehazingcited by 18
  6. 2023Frequency Compensated Diffusion Model for Real-scene Dehazingcited by 17
  7. 2021A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learningcited by 16
  8. 2023SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazingcited by 15
  9. 2025Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Visioncited by 14
  10. 2025Residual Diffusion Bridge Model for Image Restorationcited by 14
  11. 2021Efficient and Accurate Multi-scale Topological Network for Single Image Dehazingcited by 13
  12. 2023Let Segment Anything Help Image Dehazecited by 13
  13. 2024GenDeg: Diffusion-based Degradation Synthesis for Generalizable All-In-One Image Restorationcited by 13
  14. 2023Prompt-based test-time real image dehazing: a novel pipelinecited by 12
  15. 2023High-quality Image Dehazing with Diffusion Modelcited by 11
  16. 2024DehazeDCT: Towards Effective Non-Homogeneous Dehazing via Deformable Convolutional Transformercited by 10
  17. 2025Reversing Flow for Image Restorationcited by 10
  18. 2022A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truthcited by 9
  19. 2024UMCFuse: A Unified Multiple Complex Scenes Infrared and Visible Image Fusion Frameworkcited by 9
  20. 2024SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Drivingcited by 9
  21. 2024NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challengecited by 9
  22. 2025FoundIR-v2: Optimizing Pre-Training Data Mixtures for Image Restoration Foundation Modelcited by 9
  23. 2021Complementary Feature Enhanced Network with Vision Transformer for Image Dehazingcited by 8
  24. 2024Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistancecited by 8
  25. 2025Unleashing the Potential of the Semantic Latent Space in Diffusion Models for Image Dehazingcited by 8
  26. 2026CLIP-Guided Data Augmentation for Night-Time Image Dehazingcited by 8
  27. 2021Non-Homogeneous Haze Removal via Artificial Scene Prior and Bidimensional Graph Reasoningcited by 6
  28. 2025PHATNet: A Physics-guided Haze Transfer Network for Domain-adaptive Real-world Image Dehazingcited by 6
  29. 2026From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmarkcited by 6
  30. 2024VIFNet: An End-to-end Visible-Infrared Fusion Network for Image Dehazingcited by 5
  31. 2024Deep Variational Bayesian Modeling of Haze Degradation Processcited by 5
  32. 2025DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restorationcited by 5
  33. 2025UniSER: A Foundation Model for Unified Soft Effects Removalcited by 5
  34. 2023Reliable Image Dehazing by NeRFcited by 4
  35. 2024Emphasizing Crucial Features for Efficient Image Restorationcited by 4
  36. 2024Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalizationcited by 4
  37. 2025FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image Restorationcited by 4
  38. 2025HazeFlow: Revisit Haze Physical Model as ODE and Non-Homogeneous Haze Generation for Real-World Dehazingcited by 4

50 most cited of 108 All 108 (JSON)