mlsanityData to 7 Oct 2026

Progressive Image Deraining Networks: A Better and Simpler Baseline

arXiv 1901.09221 ↗First posted 26 Jan 2019cs.CVcited by 271

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Cited by 22 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Along with the deraining performance improvement of deep networks, their structures and learning become more and more complicated and diverse, making it difficult to analyze the contribution of various network modules when developing new deraining networks. To handle this issue, this paper provides a better and simpler baseline deraining network by considering network architecture, input and output, and loss functions. Specifically, by repeatedly unfolding a shallow ResNet, progressive ResNet (PRN) is proposed to take advantage of recursive computation. A recurrent layer is further introduced to exploit the dependencies of deep features across stages, forming our progressive recurrent network (PReNet). Furthermore, intra-stage recursive computation of ResNet can be adopted in PRN and PReNet to notably reduce network parameters with graceful degradation in deraining performance. For network input and output, we take both stage-wise result and original rainy image as input to each ResNet and finally output the prediction of {residual image}. As for loss functions, single MSE or negative SSIM losses are sufficient to train PRN and PReNet. Experiments show that PRN and PReNet perform favorably on both synthetic and real rainy images. Considering its simplicity, efficiency and effectiveness, our models are expected to serve as a suitable baseline in future deraining research. The source codes are available at https://github.com/csdwren/PReNet.

Key facts. Cited by 271 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jan 2019.

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Citing papers per year: 2021: 39; 2022: 44; 2023: 45; 2024: 74; 2025: 45; 2026: 24.

271 papers.

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  1. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  2. 2021Uformer: A General U-Shaped Transformer for Image Restorationcited by 864
  3. 2021Multi-Stage Progressive Image Restorationcited by 813
  4. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 301
  5. 2021HINet: Half Instance Normalization Network for Image Restorationcited by 236
  6. 2023Learning A Sparse Transformer Network for Effective Image Derainingcited by 204
  7. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 182
  8. 2022Deep Generalized Unfolding Networks for Image Restorationcited by 119
  9. 2023Controlling Vision-Language Models for Multi-Task Image Restorationcited by 108
  10. 2024AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulationcited by 108
  11. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  12. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
38 more
  1. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  2. 2023Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Modelscited by 86
  3. 2021Spatially-Adaptive Image Restoration using Distortion-Guided Networkscited by 77
  4. 2024Complexity Experts are Task-Discriminative Learners for Any Image Restorationcited by 72
  5. 2021On Efficient Transformer-Based Image Pre-training for Low-Level Visioncited by 64
  6. 2021Structure-Preserving Deraining with Residue Channel Prior Guidancecited by 63
  7. 2021Unpaired Deep Image Deraining Using Dual Contrastive Learningcited by 60
  8. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  9. 2024FreqMamba: Viewing Mamba from a Frequency Perspective for Image Derainingcited by 57
  10. 2023A Comparative Study of Image Restoration Networks for General Backbone Network Designcited by 56
  11. 2024RainMamba: Enhanced Locality Learning with State Space Models for Video Derainingcited by 56
  12. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  13. 2024Bidirectional Multi-Scale Implicit Neural Representations for Image Derainingcited by 54
  14. 2022Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyondcited by 48
  15. 2023Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streakscited by 45
  16. 2022Toward Real-world Single Image Deraining: A New Benchmark and Beyondcited by 40
  17. 2024U-shaped Vision Mamba for Single Image Dehazingcited by 40
  18. 2023From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removalcited by 39
  19. 2021Closing the Loop: Joint Rain Generation and Removal via Disentangled Image Translationcited by 36
  20. 2023Improving Image Restoration through Removing Degradations in Textual Representationscited by 36
  21. 2024RobustSAM: Segment Anything Robustly on Degraded Imagescited by 36
  22. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  23. 2023Towards Unified Deep Image Deraining: A Survey and A New Benchmarkcited by 34
  24. 2023KBNet: Kernel Basis Network for Image Restorationcited by 33
  25. 2021Robust Representation Learning with Feedback for Single Image Derainingcited by 32
  26. 2021SketchEdit: Mask-Free Local Image Manipulation with Partial Sketchescited by 32
  27. 2024FourierMamba: Fourier Learning Integration with State Space Models for Image Derainingcited by 32
  28. 2021Semi-Supervised Video Deraining with Dynamical Rain Generatorcited by 31
  29. 2022Deep Fourier Up-Samplingcited by 27
  30. 2025Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restorationcited by 27
  31. 2022DRT: A Lightweight Single Image Deraining Recursive Transformercited by 26
  32. 2021Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removalcited by 24
  33. 2024Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraintcited by 24
  34. 2023Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagationcited by 21
  35. 2024Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restorationcited by 21
  36. 2023Sign Language Translation with Iterative Prototypecited by 20
  37. 2025WeatherBench: A Real-World Benchmark Dataset for All-in-One Adverse Weather Image Restorationcited by 20
  38. 2024DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environmentscited by 19

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