mlsanityData to 7 Oct 2026

A Neural Approach to Blind Motion Deblurring

arXiv 1603.04771 ↗First posted 15 Mar 2016cs.CVcited by 69

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Abstract (arXiv)

We present a new method for blind motion deblurring that uses a neural network trained to compute estimates of sharp image patches from observations that are blurred by an unknown motion kernel. Instead of regressing directly to patch intensities, this network learns to predict the complex Fourier coefficients of a deconvolution filter to be applied to the input patch for restoration. For inference, we apply the network independently to all overlapping patches in the observed image, and average its outputs to form an initial estimate of the sharp image. We then explicitly estimate a single global blur kernel by relating this estimate to the observed image, and finally perform non-blind deconvolution with this kernel. Our method exhibits accuracy and robustness close to state-of-the-art iterative methods, while being much faster when parallelized on GPU hardware.

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Mar 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 16; 2022: 18; 2023: 7; 2024: 15; 2025: 11; 2026: 2.

69 papers.

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  1. 2021Rethinking Coarse-to-Fine Approach in Single Image Deblurringcited by 324
  2. 2021Deblurring via Stochastic Refinementcited by 248
  3. 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
  4. 2022Deep Image Deblurring: A Surveycited by 94
  5. 2021Explore Image Deblurring via Blur Kernel Spacecited by 58
  6. 2024DarkIR: Robust Low-Light Image Restorationcited by 48
  7. 2022Flow-Guided Sparse Transformer for Video Deblurringcited by 43
  8. 2023ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Imagescited by 38
  9. 2022MSSNet: Multi-Scale-Stage Network for Single Image Deblurringcited by 31
  10. 2024Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motioncited by 29
  11. 2021MC-Blur: A Comprehensive Benchmark for Image Deblurringcited by 27
  12. 2021Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Networkcited by 25
38 more
  1. 2022Real-World Deep Local Motion Deblurringcited by 20
  2. 2024Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurringcited by 20
  3. 2022Multi-scale frequency separation network for image deblurringcited by 18
  4. 2022D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restorationcited by 14
  5. 2022PDRF: Progressively Deblurring Radiance Field for Fast and Robust Scene Reconstruction from Blurry Imagescited by 14
  6. 2022Learning Spatially Varying Pixel Exposures for Motion Deblurringcited by 12
  7. 2024DeblurGS: Gaussian Splatting for Camera Motion Blurcited by 12
  8. 2021Restoration of Video Frames from a Single Blurred Image with Motion Understandingcited by 10
  9. 2021EDPN: Enhanced Deep Pyramid Network for Blurry Image Restorationcited by 9
  10. 2023MoBluRF: Motion Deblurring Neural Radiance Fields for Blurry Monocular Videocited by 9
  11. 2025One-Step Diffusion Model for Image Motion-Deblurringcited by 9
  12. 2021Super Neuronscited by 7
  13. 2022Modular Degradation Simulation and Restoration for Under-Display Cameracited by 7
  14. 2022On Adversarial Robustness of Deep Image Deblurringcited by 7
  15. 2025CoMoGaussian: Continuous Motion-Aware Gaussian Splatting from Motion-Blurred Imagescited by 7
  16. 2021Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understandingcited by 6
  17. 2021Unfolding Taylor's Approximations for Image Restorationcited by 6
  18. 2024SMURF: Continuous Dynamics for Motion-Deblurring Radiance Fieldscited by 6
  19. 2026Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restorationcited by 6
  20. 2022Blind Image Deconvolution Using Variational Deep Image Priorcited by 5
  21. 2023Deep Richardson-Lucy Deconvolution for Low-Light Image Deblurringcited by 5
  22. 2024Deep learning in motion deblurring: current status, benchmarks and future prospectscited by 5
  23. 2024Learning to Deblur Polarized Imagescited by 5
  24. 2024Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretizationcited by 5
  25. 2025HAODiff: Human-Aware One-Step Diffusion via Dual-Prompt Guidancecited by 5
  26. 2025DINO-Detect: A Simple yet Effective Framework for Blur-Robust AI-Generated Image Detectioncited by 5
  27. 2024I2-SLAM: Inverting Imaging Process for Robust Photorealistic Dense SLAMcited by 4
  28. 2021A Deep Variational Bayesian Framework for Blind Image Deblurringcited by 3
  29. 2021LODE: Deep Local Deblurring and A New Benchmarkcited by 3
  30. 2022Training Adaptive Reconstruction Networks for Blind Inverse Problemscited by 3
  31. 2024Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encodingcited by 3
  32. 2023A survey on facial image deblurringcited by 2
  33. 2023A Comprehensive Survey on Deep Neural Image Deblurringcited by 2
  34. 2024DiffLoss: unleashing diffusion model as constraint for training image restoration networkcited by 2
  35. 2024CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Imagescited by 2
  36. 2025DarkDeblur: Learning single-shot image deblurring in low-light conditioncited by 2
  37. 2021Deep Camera Obscura: An Image Restoration Pipeline for Lensless Pinhole Photographycited by 1
  38. 2021Learning Discriminative Shrinkage Deep Networks for Image Deconvolutioncited by 1

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