mlsanityData to 7 Oct 2026

Deblurring by Realistic Blurring

arXiv 2004.01860 ↗First posted 4 Apr 2020cs.CVcited by 187

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Abstract (arXiv)

Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios with sufficient accuracy. To address this problem, we propose a new method which combines two GAN models, i.e., a learning-to-Blur GAN (BGAN) and learning-to-DeBlur GAN (DBGAN), in order to learn a better model for image deblurring by primarily learning how to blur images. The first model, BGAN, learns how to blur sharp images with unpaired sharp and blurry image sets, and then guides the second model, DBGAN, to learn how to correctly deblur such images. In order to reduce the discrepancy between real blur and synthesized blur, a relativistic blur loss is leveraged. As an additional contribution, this paper also introduces a Real-World Blurred Image (RWBI) dataset including diverse blurry images. Our experiments show that the proposed method achieves consistently superior quantitative performance as well as higher perceptual quality on both the newly proposed dataset and the public GOPRO dataset.

Key facts. Cited by 187 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Apr 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 34; 2022: 37; 2023: 32; 2024: 52; 2025: 20; 2026: 12.

187 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. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
  6. 2021HINet: Half Instance Normalization Network for Image Restorationcited by 236
  7. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 182
  8. 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
  9. 2022Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Methodcited by 174
  10. 2023Efficient and Explicit Modelling of Image Hierarchies for Image Restorationcited by 145
  11. 2022Stripformer: Strip Transformer for Fast Image Deblurringcited by 139
  12. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 139
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  1. 2022Deep Generalized Unfolding Networks for Image Restorationcited by 119
  2. 2023PromptIR: Prompting for All-in-One Blind Image Restorationcited by 113
  3. 2024AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulationcited by 108
  4. 2022LEDNet: Joint Low-light Enhancement and Deblurring in the Darkcited by 95
  5. 2022Deep Image Deblurring: A Surveycited by 94
  6. 2023Hierarchical Integration Diffusion Model for Realistic Image Deblurringcited by 87
  7. 2021Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priorscited by 82
  8. 2023MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazingcited by 81
  9. 2021Intriguing Findings of Frequency Selection for Image Deblurringcited by 80
  10. 2021Spatially-Adaptive Image Restoration using Distortion-Guided Networkscited by 77
  11. 2022Multiscale Structure Guided Diffusion for Image Deblurringcited by 76
  12. 2021Improving Image Restoration by Revisiting Global Information Aggregationcited by 60
  13. 2021ARVo: Learning All-Range Volumetric Correspondence for Video Deblurringcited by 54
  14. 2022Realistic Blur Synthesis for Learning Image Deblurringcited by 51
  15. 2021BANet: Blur-aware Attention Networks for Dynamic Scene Deblurringcited by 44
  16. 2024MaIR: A Locality- and Continuity-Preserving Mamba for Image Restorationcited by 43
  17. 2022Learning Dual Memory Dictionaries for Blind Face Restorationcited by 40
  18. 2025Degradation-Aware Feature Perturbation for All-in-One Image Restorationcited by 39
  19. 2023ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Imagescited by 38
  20. 2023Improving Image Restoration through Removing Degradations in Textual Representationscited by 36
  21. 2025MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restorationcited by 36
  22. 2022Learning Degradation Representations for Image Deblurringcited by 35
  23. 2022Do better ImageNet classifiers assess perceptual similarity better?cited by 34
  24. 2022BALF: Simple and Efficient Blur Aware Local Feature Detectorcited by 34
  25. 2024FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurringcited by 28
  26. 2021MC-Blur: A Comprehensive Benchmark for Image Deblurringcited by 27
  27. 2021SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurringcited by 26
  28. 2024Position: Measure Dataset Diversity, Don't Just Claim Itcited by 26
  29. 2021Event-guided Deblurring of Unknown Exposure Time Videoscited by 25
  30. 2024Learning Enriched Features via Selective State Spaces Model for Efficient Image Deblurringcited by 25
  31. 2024AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurringcited by 25
  32. 2021Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removalcited by 24
  33. 2022RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmarkcited by 24
  34. 2023DiffI2I: Efficient Diffusion Model for Image-to-Image Translationcited by 24
  35. 2023Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurringcited by 24
  36. 2024CU-Mamba: Selective State Space Models with Channel Learning for Image Restorationcited by 24
  37. 2021Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancementcited by 23
  38. 2024UniProcessor: A Text-induced Unified Low-level Image Processorcited by 22

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