mlsanityData to 7 Oct 2026

MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing

arXiv 2207.05621 ↗First posted 12 Jul 2022cs.CVcited by 39

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Abstract (arXiv)

Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to learn effective snow removal. In order to handle the diverse scenes, we propose a multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degradation features in a multi-path manner, and integrates comprehensive scene context information for clean reconstruction via self-attention operation. For the local details of various snow degradations, the local capture module is introduced in parallel to assist in the rebuilding of a clean image. Such design achieves the SOTA performance on three desnowing benchmark datasets while costing the low parameters and computational complexity, providing a guarantee of practicality.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 30 of its 48 references that are in the map. First posted on arXiv 12 Jul 2022.

Builds on

30 of 48 references.

References · 30

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  5. 2020End-to-End Object Detection with Transformerscited by 7,384
  6. 2017Squeeze-and-Excitation Networkscited by 4,763
  7. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  8. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  9. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  10. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  11. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,552
  12. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,218
18 more
  1. 2021Swin Transformer V2: Scaling Up Capacity and Resolutioncited by 1,215
  2. 2021Video Swin Transformercited by 1,090
  3. 2021CvT: Introducing Convolutions to Vision Transformerscited by 946
  4. 2021Uformer: A General U-Shaped Transformer for Image Restorationcited by 864
  5. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  6. 2021LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inferencecited by 475
  7. 2021Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysiscited by 418
  8. 2017Relation Networks for Object Detectioncited by 305
  9. 2018Fast Online Object Tracking and Segmentation: A Unifying Approachcited by 272
  10. 2021TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditionscited by 243
  11. 2021Mobile-Former: Bridging MobileNet and Transformercited by 234
  12. 2017DesnowNet: Context-Aware Deep Network for Snow Removalcited by 200
  13. 2021MPViT: Multi-Path Vision Transformer for Dense Predictioncited by 122
  14. 2021Shunted Self-Attention via Multi-Scale Token Aggregationcited by 90
  15. 2021Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priorscited by 82
  16. 2018Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazingcited by 79
  17. 2022Underwater Light Field Retention : Neural Rendering for Underwater Imagingcited by 22
  18. 2022Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cyclecited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 13; 2025: 10; 2026: 7.

39 papers.

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  1. 2023EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animationcited by 141
  2. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
  3. 2023Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Modelcited by 69
  4. 2023Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streakscited by 45
  5. 2023Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolutioncited by 39
  6. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  7. 2024Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraintcited by 24
  8. 2023Five A+ Network: You Only Need 9K Parameters for Underwater Image Enhancementcited by 22
  9. 2023NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformercited by 19
  10. 2024VersaT2I: Improving Text-to-Image Models with Versatile Rewardcited by 17
  11. 2024Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removalcited by 17
  12. 2024AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancementcited by 16
27 more
  1. 2023Mixed Hierarchy Network for Image Restorationcited by 14
  2. 2025Controllable Weather Synthesis and Removal with Video Diffusion Modelscited by 11
  3. 2025Intra and Inter Parser-Prompted Transformers for Effective Image Restorationcited by 10
  4. 2023DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenescited by 9
  5. 2024Emphasizing Crucial Features for Efficient Image Restorationcited by 4
  6. 2024Unsupervised Low-light Image Enhancement with Lookup Tables and Diffusion Priorscited by 4
  7. 2024Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image Restorerscited by 4
  8. 2023RSFDM-Net: Real-time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancementcited by 3
  9. 2024PanAdapter: Two-Stage Fine-Tuning with Spatial-Spectral Priors Injecting for Pansharpeningcited by 3
  10. 2025Robust Adverse Weather Removal via Spectral-based Spatial Groupingcited by 3
  11. 2024How Powerful Potential of Attention on Image Restoration?cited by 1
  12. 2024Towards Context-aware Convolutional Network for Image Restorationcited by 1
  13. 2025Clear Roads, Clear Vision: Advancements in Multi-Weather Restoration for Smart Transportationcited by 1
  14. 2026Learning Adaptive Dynamical Features via Multi-τ Liquid-Mamba for All-in-one Image Restorationcited by 1
  15. 2024Parallel Cross Strip Attention Network for Single Image Dehazingcited by 0
  16. 2024Dilated Strip Attention Network for Image Restorationcited by 0
  17. 2025Wavelet-Enhanced Desnowing: A Novel Single Image Restoration Approach for Traffic Surveillance under Adverse Weather Conditionscited by 0
  18. 2025Pseudo-Label Guided Real-World Image De-weathering: A Learning Framework with Imperfect Supervisioncited by 0
  19. 2025RouteWinFormer: A Route-Window Transformer for Middle-range Attention in Image Restorationcited by 0
  20. 2025LucidFlux: Caption-Free Photo-Realistic Image Restoration via a Large-Scale Diffusion Transformercited by 0
  21. 2025Learning to Restore Multi-Degraded Images via Ingredient Decoupling and Task-Aware Path Adaptationcited by 0
  22. 2026From Physical Degradation Models to Task-Aware All-in-One Image Restorationcited by 0
  23. 2026QUSR: Quality-Aware and Uncertainty-Guided Image Super-Resolution Diffusion Modelcited by 0
  24. 2026DVANet: Degradation-aware Visual-prior Alignment Network for Image Restorationcited by 0
  25. 2026Causal-AgentIR: Self-Evolving Causal Memory for Adaptive Image Restoration Agentscited by 0
  26. 2026Ultra-High-Definition Restoration Transformers with Correlation Matching Transformationcited by 0
  27. 2026GraLoD: Graphics-Inspired Continuous Level-of-Detail Learning for Image Restorationcited by 0