mlsanityData to 7 Oct 2026

DesnowNet: Context-Aware Deep Network for Snow Removal

arXiv 1708.04512 ↗First posted 15 Aug 2017cs.CVcited by 200

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Cited by 31 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Existing learning-based atmospheric particle-removal approaches such as those used for rainy and hazy images are designed with strong assumptions regarding spatial frequency, trajectory, and translucency. However, the removal of snow particles is more complicated because it possess the additional attributes of particle size and shape, and these attributes may vary within a single image. Currently, hand-crafted features are still the mainstream for snow removal, making significant generalization difficult to achieve. In response, we have designed a multistage network codenamed DesnowNet to in turn deal with the removal of translucent and opaque snow particles. We also differentiate snow into attributes of translucency and chromatic aberration for accurate estimation. Moreover, our approach individually estimates residual complements of the snow-free images to recover details obscured by opaque snow. Additionally, a multi-scale design is utilized throughout the entire network to model the diversity of snow. As demonstrated in experimental results, our approach outperforms state-of-the-art learning-based atmospheric phenomena removal methods and one semantic segmentation baseline on the proposed Snow100K dataset in both qualitative and quantitative comparisons. The results indicate our network would benefit applications involving computer vision and graphics.

Key facts. Cited by 200 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Aug 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 16; 2023: 20; 2024: 53; 2025: 59; 2026: 44.

200 papers.

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  1. 2021TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditionscited by 243
  2. 2022Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Modelscited by 215
  3. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  4. 2023Controlling Vision-Language Models for Multi-Task Image Restorationcited by 108
  5. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
  6. 2021Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priorscited by 82
  7. 2023MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazingcited by 81
  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. 2023GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditionscited by 62
  12. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
38 more
  1. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  2. 2024Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Taskscited by 47
  3. 2024PromptFix: You Prompt and We Fix the Photocited by 40
  4. 2022MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowingcited by 39
  5. 2025UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Priorcited by 39
  6. 2023Language-driven All-in-one Adverse Weather Removalcited by 36
  7. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  8. 2025JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restorationcited by 32
  9. 2024PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructionscited by 31
  10. 2023ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Renderingcited by 28
  11. 2022DRT: A Lightweight Single Image Deraining Recursive Transformercited by 26
  12. 2025Visual-Instructed Degradation Diffusion for All-in-One Image Restorationcited by 26
  13. 2024Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraintcited by 24
  14. 2024MWFormer: Multi-Weather Image Restoration Using Degradation-Aware Transformerscited by 24
  15. 2023Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagationcited by 21
  16. 2025Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Datacited by 21
  17. 2025WeatherBench: A Real-World Benchmark Dataset for All-in-One Adverse Weather Image Restorationcited by 20
  18. 2021Blind Image Decompositioncited by 18
  19. 2024Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restorationcited by 18
  20. 2024AWRaCLe: All-Weather Image Restoration using Visual In-Context Learningcited by 18
  21. 2024LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restorationcited by 18
  22. 2024Beyond Pixels: Text Enhances Generalization in Real-World Image Restorationcited by 17
  23. 2024Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restorationcited by 15
  24. 2025RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restorationcited by 15
  25. 2023Mixed Hierarchy Network for Image Restorationcited by 14
  26. 2024Sharing Key Semantics in Transformer Makes Efficient Image Restorationcited by 14
  27. 2025Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Visioncited by 14
  28. 2025Residual Diffusion Bridge Model for Image Restorationcited by 14
  29. 2022Snow Mask Guided Adaptive Residual Network for Image Snow Removalcited by 13
  30. 2022SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowingcited by 13
  31. 2024Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structurecited by 13
  32. 2024All-in-one Weather-degraded Image Restoration via Adaptive Degradation-aware Self-prompting Modelcited by 13
  33. 2024GenDeg: Diffusion-based Degradation Synthesis for Generalizable All-In-One Image Restorationcited by 13
  34. 2024WeatherGS: 3D Scene Reconstruction in Adverse Weather Conditions via Gaussian Splattingcited by 13
  35. 2023Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removalcited by 12
  36. 2024Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removalcited by 12
  37. 2024UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularitycited by 12
  38. 2023WM-MoE: Weather-aware Multi-scale Mixture-of-Experts for Blind Adverse Weather Removalcited by 11

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