mlsanityData to 7 Oct 2026

Rethinking Coarse-to-Fine Approach in Single Image Deblurring

arXiv 2108.05054 ↗First posted 11 Aug 2021cs.CV cs.AIcited by 324

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Cited by 23 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Coarse-to-fine strategies have been extensively used for the architecture design of single image deblurring networks. Conventional methods typically stack sub-networks with multi-scale input images and gradually improve sharpness of images from the bottom sub-network to the top sub-network, yielding inevitably high computational costs. Toward a fast and accurate deblurring network design, we revisit the coarse-to-fine strategy and present a multi-input multi-output U-net (MIMO-UNet). The MIMO-UNet has three distinct features. First, the single encoder of the MIMO-UNet takes multi-scale input images to ease the difficulty of training. Second, the single decoder of the MIMO-UNet outputs multiple deblurred images with different scales to mimic multi-cascaded U-nets using a single U-shaped network. Last, asymmetric feature fusion is introduced to merge multi-scale features in an efficient manner. Extensive experiments on the GoPro and RealBlur datasets demonstrate that the proposed network outperforms the state-of-the-art methods in terms of both accuracy and computational complexity. Source code is available for research purposes at https://github.com/chosj95/MIMO-UNet.

Key facts. Cited by 324 papers in the map (data through 7 Oct 2026). Builds on 19 of its 38 references that are in the map. First posted on arXiv 11 Aug 2021.

Builds on

19 of 38 references.

References · 19

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  3. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  4. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,543
  5. 2021Multi-Stage Progressive Image Restorationcited by 813
  6. 2016Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurringcited by 722
  7. 2017DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networkscited by 366
  8. 2019DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Bettercited by 361
  9. 2018Scale-recurrent Network for Deep Image Deblurringcited by 332
  10. 2019Deep Stacked Hierarchical Multi-patch Network for Image Deblurringcited by 205
  11. 2020Human-Aware Motion Deblurringcited by 174
  12. 2017DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networkscited by 156
7 more
  1. 2015Learning a Convolutional Neural Network for Non-uniform Motion Blur Removalcited by 148
  2. 2020Spatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurringcited by 119
  3. 2019Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Trainingcited by 112
  4. 2016A Neural Approach to Blind Motion Deblurringcited by 69
  5. 2014Learning to Deblurcited by 66
  6. 2020Image Demoireing with Learnable Bandpass Filterscited by 44
  7. 2018Spatial Frequency Loss for Learning Convolutional Autoencoderscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 46; 2023: 67; 2024: 97; 2025: 61; 2026: 44.

324 papers.

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  1. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  2. 2022Simple Baselines for Image Restorationcited by 701
  3. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 301
  4. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
  5. 2021Deblurring via Stochastic Refinementcited by 248
  6. 2022Efficient Frequency Domain-based Transformers for High-Quality Image Deblurringcited by 164
  7. 2023Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restorationcited by 164
  8. 2023Efficient and Explicit Modelling of Image Hierarchies for Image Restorationcited by 145
  9. 2022Stripformer: Strip Transformer for Fast Image Deblurringcited by 139
  10. 2021Event-Based Fusion for Motion Deblurring with Cross-modal Attentioncited by 112
  11. 2024AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulationcited by 108
  12. 2022LEDNet: Joint Low-light Enhancement and Deblurring in the Darkcited by 95
38 more
  1. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  2. 2023Hierarchical Integration Diffusion Model for Realistic Image Deblurringcited by 87
  3. 2021Intriguing Findings of Frequency Selection for Image Deblurringcited by 80
  4. 2022Multiscale Structure Guided Diffusion for Image Deblurringcited by 76
  5. 2024Efficient Diffusion Model for Image Restoration by Residual Shiftingcited by 64
  6. 2023GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditionscited by 62
  7. 2025HVI: A New Color Space for Low-light Image Enhancementcited by 62
  8. 2021Improving Image Restoration by Revisiting Global Information Aggregationcited by 60
  9. 2024The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Reportcited by 57
  10. 2023A Comparative Study of Image Restoration Networks for General Backbone Network Designcited by 56
  11. 2024Bidirectional Multi-Scale Implicit Neural Representations for Image Derainingcited by 54
  12. 2022Realistic Blur Synthesis for Learning Image Deblurringcited by 51
  13. 2022READ: Large-Scale Neural Scene Rendering for Autonomous Drivingcited by 50
  14. 2024DarkIR: Robust Low-Light Image Restorationcited by 48
  15. 2024Frequency-Assisted Mamba for Remote Sensing Image Super-Resolutioncited by 47
  16. 2023WaveDM: Wavelet-Based Diffusion Models for Image Restorationcited by 46
  17. 2022ShuffleMixer: An Efficient ConvNet for Image Super-Resolutioncited by 44
  18. 2023Prompt-In-Prompt Learning for Universal Image Restorationcited by 43
  19. 2024MaIR: A Locality- and Continuity-Preserving Mamba for Image Restorationcited by 43
  20. 2024BAGS: Blur Agnostic Gaussian Splatting through Multi-Scale Kernel Modelingcited by 42
  21. 2024RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Modelscited by 41
  22. 2022NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Resultscited by 40
  23. 2024Correlation Matching Transformation Transformers for UHD Image Restorationcited by 39
  24. 2025Degradation-Aware Feature Perturbation for All-in-One Image Restorationcited by 39
  25. 2023ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Imagescited by 38
  26. 2023Improving Image Restoration through Removing Degradations in Textual Representationscited by 36
  27. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  28. 2022Learning Degradation Representations for Image Deblurringcited by 35
  29. 2022Geometry-aware Single-image Full-body Human Relightingcited by 34
  30. 2023KBNet: Kernel Basis Network for Image Restorationcited by 33
  31. 2022MSSNet: Multi-Scale-Stage Network for Single Image Deblurringcited by 31
  32. 2021MC-Blur: A Comprehensive Benchmark for Image Deblurringcited by 27
  33. 2024Efficient Visual State Space Model for Image Deblurringcited by 27
  34. 2025Visual-Instructed Degradation Diffusion for All-in-One Image Restorationcited by 26
  35. 2021Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurringcited by 25
  36. 2021Event-guided Deblurring of Unknown Exposure Time Videoscited by 25
  37. 2024Learning Enriched Features via Selective State Spaces Model for Efficient Image Deblurringcited by 25
  38. 2024AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurringcited by 25

50 most cited of 324 All 324 (JSON)