mlsanityData to 7 Oct 2026

Learning to Deblur

arXiv 1406.7444 ↗First posted 28 Jun 2014cs.CV cs.LGcited by 66

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Abstract (arXiv)

We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, and parts of which incorporate computations that are specific to image deconvolution. The system is trained end-to-end on a set of artificially generated training examples, enabling competitive performance in blind deconvolution, both with respect to quality and runtime.

Key facts. Cited by 66 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jun 2014.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 25; 2023: 7; 2024: 5; 2025: 12; 2026: 4.

66 papers.

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  1. 2021Rethinking Coarse-to-Fine Approach in Single Image Deblurringcited by 324
  2. 2022Parallel Diffusion Models of Operator and Image for Blind Inverse Problemscited by 113
  3. 2022Deep Image Deblurring: A Surveycited by 94
  4. 2023Hierarchical Integration Diffusion Model for Realistic Image Deblurringcited by 87
  5. 2021Explore Image Deblurring via Blur Kernel Spacecited by 58
  6. 2022Equivariant Hypergraph Diffusion Neural Operatorscited by 45
  7. 2022Learning Degradation Representations for Image Deblurringcited by 35
  8. 2022BALF: Simple and Efficient Blur Aware Local Feature Detectorcited by 34
  9. 2022MSSNet: Multi-Scale-Stage Network for Single Image Deblurringcited by 31
  10. 2022Theoretical Perspectives on Deep Learning Methods in Inverse Problemscited by 22
  11. 2021Gaussian Kernel Mixture Network for Single Image Defocus Deblurringcited by 20
  12. 2022Real-World Deep Local Motion Deblurringcited by 20
38 more
  1. 2024Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurringcited by 20
  2. 2022Multi-scale frequency separation network for image deblurringcited by 18
  3. 2023Optical Aberration Correction in Postprocessing using Imaging Simulationcited by 18
  4. 2022Self-Supervised Image Restoration with Blurry and Noisy Pairscited by 17
  5. 2021Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurringcited by 16
  6. 2021Stable and Interpretable Unrolled Dictionary Learningcited by 15
  7. 2023Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurringcited by 13
  8. 2022Learning Spatially Varying Pixel Exposures for Motion Deblurringcited by 12
  9. 2022Deep Model-Based Super-Resolution with Non-uniform Blurcited by 10
  10. 2022Blind Image Deblurring with Unknown Kernel Size and Substantial Noisecited by 10
  11. 2023MoBluRF: Motion Deblurring Neural Radiance Fields for Blurry Monocular Videocited by 9
  12. 2025One-Step Diffusion Model for Image Motion-Deblurringcited by 9
  13. 2021Super Neuronscited by 7
  14. 2022On Adversarial Robustness of Deep Image Deblurringcited by 7
  15. 2021Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understandingcited by 6
  16. 2022Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-trainingcited by 5
  17. 2024Deep learning in motion deblurring: current status, benchmarks and future prospectscited by 5
  18. 2024Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretizationcited by 5
  19. 2025Learning few-step posterior samplers by unfolding and distillation of diffusion modelscited by 5
  20. 2021A Deep Variational Bayesian Framework for Blind Image Deblurringcited by 3
  21. 2022Training Adaptive Reconstruction Networks for Blind Inverse Problemscited by 3
  22. 2023Hierarchical Optimization-Derived Learningcited by 3
  23. 2024Efficient Image Deblurring Networks based on Diffusion Modelscited by 3
  24. 2021Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networkscited by 2
  25. 2022Robust Scene Inference under Noise-Blur Dual Corruptionscited by 2
  26. 2023A survey on facial image deblurringcited by 2
  27. 2023A Comprehensive Survey on Deep Neural Image Deblurringcited by 2
  28. 2025DarkDeblur: Learning single-shot image deblurring in low-light conditioncited by 2
  29. 2025Efficient RAW Image Deblurring with Adaptive Frequency Modulationcited by 2
  30. 2021Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolutioncited by 1
  31. 2021SL-CycleGAN: Blind Motion Deblurring in Cycles using Sparse Learningcited by 1
  32. 2021Survey of Deep Learning Methods for Inverse Problemscited by 1
  33. 2022Deblurring Photographs of Characters Using Deep Neural Networkscited by 1
  34. 2022Multi-Outputs Is All You Need For Deblurcited by 1
  35. 2022Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Networkcited by 1
  36. 2022NFResNet: Multi-scale and U-shaped Networks for Deblurringcited by 1
  37. 2025Reconstruct Anything Model: a lightweight general model for computational imagingcited by 1
  38. 2021Tracking Based Semi-Automatic Annotation for Scene Text Videoscited by 0

50 most cited of 66 All 66 (JSON)