mlsanityData to 7 Oct 2026

Deep Joint Rain Detection and Removal from a Single Image

arXiv 1609.07769 ↗First posted 25 Sep 2016cs.CVcited by 351

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Cited by 42 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper, we address a rain removal problem from a single image, even in the presence of heavy rain and rain streak accumulation. Our core ideas lie in the new rain image models and a novel deep learning architecture. We first modify an existing model comprising a rain streak layer and a background layer, by adding a binary map that locates rain streak regions. Second, we create a new model consisting of a component representing rain streak accumulation (where individual streaks cannot be seen, and thus visually similar to mist or fog), and another component representing various shapes and directions of overlapping rain streaks, which usually happen in heavy rain. Based on the first model, we develop a multi-task deep learning architecture that learns the binary rain streak map, the appearance of rain streaks, and the clean background, which is our ultimate output. The additional binary map is critically beneficial, since its loss function can provide additional strong information to the network. To handle rain streak accumulation (again, a phenomenon visually similar to mist or fog) and various shapes and directions of overlapping rain streaks, we propose a recurrent rain detection and removal network that removes rain streaks and clears up the rain accumulation iteratively and progressively. In each recurrence of our method, a new contextualized dilated network is developed to exploit regional contextual information and outputs better representation for rain detection. The evaluation on real images, particularly on heavy rain, shows the effectiveness of our novel models and architecture, outperforming the state-of-the-art methods significantly. Our codes and data sets will be publicly available.

Key facts. Cited by 351 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Sep 2016.

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Citing papers per year: 2021: 35; 2022: 50; 2023: 52; 2024: 86; 2025: 79; 2026: 49.

351 papers.

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  1. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  2. 2021Multi-Stage Progressive Image Restorationcited by 813
  3. 2022Images Speak in Images: A Generalist Painter for In-Context Visual Learningcited by 317
  4. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 301
  5. 2021HINet: Half Instance Normalization Network for Image Restorationcited by 236
  6. 2022Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Modelscited by 215
  7. 2023Learning A Sparse Transformer Network for Effective Image Derainingcited by 204
  8. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 182
  9. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  10. 2022Deep Generalized Unfolding Networks for Image Restorationcited by 119
  11. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  12. 2023Controlling Vision-Language Models for Multi-Task Image Restorationcited by 108
38 more
  1. 2022ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removalcited by 102
  2. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  3. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
  4. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  5. 2021Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priorscited by 82
  6. 2021Spatially-Adaptive Image Restoration using Distortion-Guided Networkscited by 77
  7. 2023ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restorationcited by 77
  8. 2024Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Modelcited by 73
  9. 2024Diffusion Models in Low-Level Vision: A Surveycited by 73
  10. 2024Restoring Images in Adverse Weather Conditions via Histogram Transformercited by 73
  11. 2021Structure-Preserving Deraining with Residue Channel Prior Guidancecited by 63
  12. 2023GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditionscited by 62
  13. 2021Unpaired Deep Image Deraining Using Dual Contrastive Learningcited by 60
  14. 2024Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restorationcited by 60
  15. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  16. 2024FreqMamba: Viewing Mamba from a Frequency Perspective for Image Derainingcited by 57
  17. 2023A Comparative Study of Image Restoration Networks for General Backbone Network Designcited by 56
  18. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  19. 2024Bidirectional Multi-Scale Implicit Neural Representations for Image Derainingcited by 54
  20. 2022Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyondcited by 48
  21. 2024Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Taskscited by 47
  22. 2025Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modelingcited by 47
  23. 2023Neural Degradation Representation Learning for All-In-One Image Restorationcited by 46
  24. 2023Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streakscited by 45
  25. 2023Prompt-In-Prompt Learning for Universal Image Restorationcited by 43
  26. 2023Image Restoration Through Generalized Ornstein-Uhlenbeck Bridgecited by 41
  27. 2022Toward Real-world Single Image Deraining: A New Benchmark and Beyondcited by 40
  28. 2024U-shaped Vision Mamba for Single Image Dehazingcited by 40
  29. 2023From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removalcited by 39
  30. 2025UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Priorcited by 39
  31. 2021Closing the Loop: Joint Rain Generation and Removal via Disentangled Image Translationcited by 36
  32. 2023Improving Image Restoration through Removing Degradations in Textual Representationscited by 36
  33. 2024RobustSAM: Segment Anything Robustly on Degraded Imagescited by 36
  34. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  35. 2023Towards Unified Deep Image Deraining: A Survey and A New Benchmarkcited by 34
  36. 2021Robust Representation Learning with Feedback for Single Image Derainingcited by 32
  37. 2024FourierMamba: Fourier Learning Integration with State Space Models for Image Derainingcited by 32
  38. 2021Semi-Supervised Video Deraining with Dynamical Rain Generatorcited by 31

50 most cited of 351 All 351 (JSON)