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Awesome-Deblurring
A curated list of resources for Image and Video Deblurring
https://github.com/subeeshvasu/Awesome-Deblurring
Last synced: 4 days ago
JSON representation
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Non-Blind-Deblurring
- Fast image deconvolution using hyper-laplacian priors - deconvolution/)|
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Richardson-Lucy Deblurring for Scenes under a Projective Motion Path
- Handling outliers in non-blind image deconvolution
- From learning models of natural image patches to whole image restoration
- Bm3d frames and variational image deblurring
- Robust image deblurring with an inaccurate blur kernel
- A machine learning approach for non-blind image deconvolution
- Discriminative non-blind deblurring - darmstadt.de/vi_research/code/index.en.jsp#discriminative_deblurring)|
- A general framework for regularized, similarity-based image restoration
- Deep convolutional neural network for image deconvolution
- Shrinkage fields for effective image restoration - fields)|
- Good Image Priors for Non-blind Deconvolution: Generic vs Specific
- Fast Non-Blind Image De-blurring With Sparse Priors
- Partial Deconvolution With Inaccurate Blur Kernel
- Fast non-blind deconvolution via regularized residual networks with long/short skip-connections
- Noise-Blind Image Deblurring
- Learning Deep CNN Denoiser Prior for Image Restoration
- Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution
- Learning proximal operators: Using denoising networks for regularizing inverse imaging problems
- Learning to push the limits of efficient fft-based image deconvolution - deconvolution-network)|
- Deep Mean-Shift Priors for Image Restoration
- Modeling Realistic Degradations in Non-Blind Deconvolution
- Non-blind Deblurring: Handling Kernel Uncertainty with CNNs - on-benchmark-datasets](https://github.com/subeeshvasu/2018_subeesh_nbd_cvpr)|
- Deep image prior - image-prior)|
- Learning Data Terms for Non-blind Deblurring
- Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation - GLRA)|
- Deep decoder: Concise image representations from untrained non-convolutional networks
- Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels
- Image deconvolution with deep image and kernel priors
- Denoising prior driven deep neural network for image restoration
- Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring - on-benchmark-datasets](https://github.com/ysnan/VEM-NBD)|
- Deep Learning for Handling Kernel/model Uncertainty in Image Deconvolution - on-benchmark-datasets](https://github.com/ysnan/NBD_KerUnc)|
- End-to-end interpretable learning of non-blind image deblurring
- Bp-dip: A backprojection based deep image prior - DIP-deblurring)|
- Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring - klsb.mpg.de/jdong/dwdn)|
- Learning deep gradient descent optimization for image deconvolution - optimizer-rgdn)|
- Neumann networks for linear inverse problems in imaging
- The Maximum Entropy on the Mean Method for Image Deblurring
- Learning Spatially-Variant MAP Models for Non-Blind Image Deblurring
- Learning a Non-Blind Deblurring Network for Night Blurry Images
- Nonblind Image Deblurring via Deep Learning in Complex Field
- Non-Blind Deblurring for Fluorescence: A Deformable Latent Space Approach With Kernel Parameterization
- A Robust Non-Blind Deblurring Method Using Deep Denoiser Prior
- Black-box image deblurring and defiltering
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Image deblurring in the presence of impulsive noise
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
- Deep Plug-and-Play Nighttime Non-Blind Deblurring With Saturated Pixel Handling Schemes
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Fast non-blind deconvolution via regularized residual networks with long/short skip-connections
- Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution
- Deep Constrained Least Squares for Blind Image Super-Resolution
- DWDN: Deep Wiener Deconvolution Network for Non-Blind Image Deblurring
- Photon Limited Non-Blind Deblurring Using Algorithm Unrolling - deblurring)|
- Wiener Guided DIP for Unsupervised Blind Image Deconvolution
- Uncertainty-Aware Unsupervised Image Deblurring with Deep Residual Prior - tang3/UAUDeblur)|
- Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
- Reverse image filtering with clean and noisy filters
- INFWIDE: Image and Feature Space Wiener Deconvolution Network for Non-blind Image Deblurring in Low-Light Conditions
- Blind Image Deconvolution Using Variational Deep Image Prior - Huo/VDIP-Deconvolution)|
- The Secrets of Non-Blind Poisson Deconvolution
- Deep Richardson-Lucy Deconvolution for Low-Light Image Deblurring
- Image deblurring in the presence of impulsive noise
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Fast Non-Blind Image De-blurring With Sparse Priors
- Fast Non-Blind Image De-blurring With Sparse Priors
- Fast Non-Blind Image De-blurring With Sparse Priors
- Reverse image filtering with clean and noisy filters
- Reverse image filtering with clean and noisy filters
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
- Image deblurring in the presence of impulsive noise
-
Single-Image-Blind-Motion-Deblurring (non-DL)
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- Removing camera shake from a single photograph
- Single image motion deblurring using transparency
- Psf estimation using sharp edge prediction - grp/research/psf_estimation/)|
- High-quality motion deblurring from a single image
- Fast motion deblurring
- Image deblurring and denoising using color priors
- Efficient ̈filter flow for space-variant multiframe blind deconvolution
- Non-uniform deblurring for shaken images
- Denoising vs. deblurring: HDR imaging techniques using moving cameras
- Single image deblurring using motion density functions
- Two-phase kernel estimation for robust motion deblurring
- Space-variant single-image blind deconvolution for removing camera shake
- Blind deconvolution using a normalized sparsity measure - deconvolution/)|
- Blur kernel estimation using the radon transform
- Exploring aligned complementary image pair for blind motion deblurring
- Fast removal of non-uniform camera shake
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- Blur-kernel estimation from spectral irregularities
- MRF-based Blind Image Deconvolution
- Framelet-based Blind Motion deblurring from a single Image
- Unnatural L0 sparse representation for natural image deblurring
- Handling noise in single image deblurring using directional filters
- Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse Penalty - uniform-camera-shake-removal)|
- Dynamic Scene Deblurring
- Segmentation-Free Dynamic Scene Deblurring
- Separable Kernel for Image Deblurring
- Hybrid Image Deblurring by Fusing Edge and Power Spectrum Information
- Deblurring Face Images with Exemplars
- Blind deblurring using internal patch recurrence
- Scale Adaptive Blind Deblurring - adaptive-blind-deblurring)|
- Kernel Fusion for Better Image Deblurring
- Class-Specific Image Deblurring - anwar/Class_Specific_Deblurring)|
- Coupled Learning for Facial Deblur
- Blind image deblurring using dark channel prior - channel-deblur/)|
- Robust Kernel Estimation with Outliers Handling for Image Deblurring
- Blind image deconvolution by automatic gradient activation
- Image deblurring via extreme channels prior
- From local to global: Edge profiles to camera motion in blurred images - on-benchmark-datasets](https://subeeshvasu.github.io/2017_subeesh_from_cvpr/)|
- Blind Image Deblurring with Outlier Handling
- Self-paced Kernel Estimation for Robust Blind Image Deblurring - 87js7KKFrIzAlushc1HJqEogR1L)|
- Convergence Analysis of MAP based Blur Kernel Estimation
- Normalized Blind Deconvolution
- Deblurring Natural Image Using Super-Gaussian Fields
- Blind Image Deblurring With Local Maximum Gradient Prior
- Phase-Only Image Based Kernel Estimation for Single Image Blind Deblurring - on-benchmark-datasets](https://github.com/panpanfei/Phase-only-Image-Based-Kernel-Estimation-for-Blind-Motion-Deblurring/tree/master/result)|
- A Variational EM Framework With Adaptive Edge Selection for Blind Motion Deblurring
- Graph-Based Blind Image Deblurring From a Single Photograph - Based-Blind-Image-Deblurring)|
- Surface-aware Blind Image Deblurring
- Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
- OID: Outlier Identifying and Discarding in Blind Image Deblurring
- Enhanced Sparse Model for Blind Deblurring
- Blind Deblurring for Saturated Images
- Polyblur: Removing mild blur by polynomial reblurring
- Fast blind deconvolution using a deeper sparse patch-wise maximum gradient prior
- Blind Image Deblurring Using Patch-Wise Minimal Pixels Regularization - pmp)|
- Pixel Screening Based Intermediate Correction for Blind Deblurring
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- Single image deblurring using motion density functions
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
- The non-parametric sub-pixel local point spread function estimation is a well posed problem
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(Multi-image/Video)-Motion-Deblurring
- Generalized Video Deblurring for Dynamic Scenes
- Image Deblurring with Blurred/Noisy Image Pairs
- Robust dual motion deblurring
- Blind motion deblurring using multiple images
- Robust flash deblurring
- Efficient filter flow for space-variant multiframe blind deconvolution
- Deconvolving PSFs for A Better Motion Deblurring using Multiple Images
- Robust multichannel blind deconvolution via fast alternating minimization
- Registration Based Non-uniform Motion Deblurring
- Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior - blind-deblurring)|
- Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution Enhancement - shot-imaging)|
- Gyro-Based Multi-Image Deconvolution for Removing Handshake Blur
- Modeling Blurred Video with Layers - blur-in-layers)|
- Hand-held video deblurring via efficient fourier aggregation
- Removing camera shake via weighted fourier burst accumulation
- Generalized Video Deblurring for Dynamic Scenes
- Intra-Frame Deblurring by Leveraging Inter-Frame Camera Motion
- Stereo video deblurring
- Simultaneous stereo video deblurring and scene flow estimation
- Light Field Blind Motion Deblurring
- Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel
- Online Video Deblurring via Dynamic Temporal Blending Network
- Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks
- Joint Blind Motion Deblurring and Depth Estimation of Light Field
- Dynamic Video Deblurring using a Locally Adaptive Linear Blur Model
- Reblur2deblur: Deblurring videos via self-supervised learning
- LSD-Joint Denoising and Deblurring of Short and Long Exposure Images with Convolutional Neural Networks
- Adversarial Spatio-Temporal Learning for Video Deblurring - Spatio-Temporal-Learning-for-Video-Deblurring)|
- Recurrent Neural Networks With Intra-Frame Iterations for Video Deblurring
- A Deep Motion Deblurring Network based on Per-Pixel Adaptive Kernels with Residual Down-Up and Up-Down Modules
- Spatio-Temporal Filter Adaptive Network for Video Deblurring
- Deep Video Deblurring: The Devil is in the Details - devil)|
- Cascaded Deep Video Deblurring Using Temporal Sharpness Prior - TSP)|[Project Page](https://baihaoran.xyz/projects/cdvd-tsp/index.html)|
- Blurry Video Frame Interpolation
- Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring - tech/ESTRNN)|
- Face Video Deblurring using 3D Facial Priors
- Deep Recurrent Network for Fast and Full-Resolution Light Field Deblurring
- Learning Event-Driven Video Deblurring and Interpolation
- Blur Removal Via Blurred-Noisy Image Pair
- Recursive Neural Network for Video Deblurring
- Motion-blurred Video Interpolation and Extrapolation
- Gated Spatio-Temporal Attention-Guided Video Deblurring
- ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
- Video Deblurring via Spatiotemporal Pyramid Network and Adversarial Gradient Prior
- Multi-Scale Separable Network for Ultra-High-Definition Video Deblurring
- Deep Recurrent Neural Network with Multi-Scale Bi-Directional Propagation for Video Deblurring
- Spatio-Temporal Deformable Attention Network for Video Deblurring
- ERDN: Equivalent Receptive Field Deformable Network for Video Deblurring
- Efficient Video Deblurring Guided by Motion Magnitude - RNN)|
- DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting
- Towards Real-World Video Deblurring by Exploring Blur Formation Process
- Real-Time Video Deblurring via Lightweight Motion Compensation
- Deep Video Deblurring for Hand-Held Cameras
- Registration Based Non-uniform Motion Deblurring
- Deep Discriminative Spatial and Temporal Network for Efficient Video Deblurring
- Exploring Temporal Frequency Spectrum in Deep Video Deblurring
- E2NeRF: Event Enhanced Neural Radiance Fields from Blurry Images
- Deblur-NSFF: Neural Scene Flow Fields for Blurry Dynamic Scenes
- Joint Video Multi-Frame Interpolation and Deblurring Under Unknown Exposure Time
- Improving Image Restoration by Revisiting Global Information Aggregation - research/TLC)|
- Deblur-NeRF: Neural Radiance Fields From Blurry Images - NeRF)|
- DP-NeRF: Deblurred Neural Radiance Field with Physical Scene Priors - NeRF)|
- BAD-NeRF: Bundle Adjusted Deblur Neural Radiance Fields - CVGL/BAD-NeRF)|
- Burst Deblurring: Removing Camera Shake Through Fourier Burst Accumulation
-
Single-Image-Blind-Motion-Deblurring (DL)
- Learning a convolutional neural network for non-uniform motion blur removal - 78101.zip),[Code 2](https://github.com/Sibozhu/MotionBlur-detection-by-CNN)|
- Convolutional neural networks for direct text deblurring - Deblur/)|
- A neural approach to blind motion deblurring
- Learning to deblur
- From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur
- Blur-Invariant Deep Learning for Blind Deblurring
- Learning to Super-resolve Blurry Face and Text Images
- Learning Discriminative Data Fitting Functions for Blind Image Deblurring
- Semi-supervised Learning of Camera Motion from a Blurred Image
- Motion blur kernel estimation via deep learning
- Deep Semantic Face Deblurring - Semantic-Face-Deblurring)|
- Learning a Discriminative Prior for Blind Image Deblurring
- Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks
- Scale-recurrent network for deep image deblurring - Deblur)|
- Deblurgan: Blind motion deblurring using conditional adversarial networks - Pytorch](https://github.com/KupynOrest/DeblurGAN)|
- Unsupervised Class-Specific Deblurring
- Gated Fusion Network for Joint Image Deblurring and Super-Resolution
- Gyroscope-Aided Motion Deblurring with Deep Networks
- Dynamic Scene Deblurring With Parameter Selective Sharing and Nested Skip Connections
- Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring - cvpr19-master)|
- Unsupervised Domain-Specific Deblurring via Disentangled Representations - Domain-Specific-Deblurring)|
- Bringing Alive Blurred Moments - on-benchmark-datasets](https://github.com/anshulbshah/Blurred-Image-to-Video)|
- Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution
- DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better - VITA/DeblurGANv2)|
- Exposure Trajectory Recovery from Motion Blur - ETR)|
- Tell Me Where It is Still Blurry: Adversarial Blurred Region Mining and Refining
- Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement - VITA/DeblurGANv2)|
- Learning to Deblur Face Images via Sketch Synthesis
- Region-Adaptive Dense Network for Efficient Motion Deblurring
- DAVID: Dual-Attentional Video Deblurring
- Neural Blind Deconvolution Using Deep Priors
- Spatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurring
- Efficient Dynamic Scene Deblurring Using Spatially Variant Deconvolution Network With Optical Flow Guided Training
- Deblurring using Analysis-Synthesis Networks Pair
- Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training
- Efficient and Interpretable Deep Blind Image Deblurring Via Algorithm Unrolling
- Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks - Face-Deblurring)|
- Dark and bright channel prior embedded network for dynamic scene deblurring
- Dynamic Scene Deblurring by Depth Guided Model
- Scale-Iterative Upscaling Network for Image Deblurring
- Human Motion Deblurring using Localized Body Prior
- Physics-Based Generative Adversarial Models for Image Restoration and Beyond
- Raw Image Deblurring
- Blur Invariant Kernel-Adaptive Network for Single Image Blind deblurring
- BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
- Multi-Stage Progressive Image Restoration
- DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
- Blind Deblurring for Saturated Images
- Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning
- Explore Image Deblurring via Encoded Blur Kernel Space - kernel-space-exploring)|
- Pre-trained image processing transformer - noah/Pretrained-IPT)|
- Multi-stage progressive image restoration
- Hinet: Half instance normalization network for image restoration - model/HINet)|
- Spatially-Adaptive Image Restoration using Distortion-Guided Networks - analysis/spatially-adaptive-image-restoration/)|
- Rethinking Coarse-To-Fine Approach in Single Image Deblurring - unet)|
- Perceptual Variousness Motion Deblurring With Light Global Context Refinement
- Pyramid Architecture Search for Real-Time Image Deblurring
- Searching for Controllable Image Restoration Networks
- Sdwnet: A straight dilated network with wavelet transformation for image deblurring
- Structure-Aware Motion Deblurring Using Multi-Adversarial Optimized CycleGAN
- Degradation Aware Approach to Image Restoration Using Knowledge Distillation
- Non-uniform Blur Kernel Estimation via Adaptive Basis Decomposition
- Clean Images are Hard to Reblur: A New Clue for Deblurring
- Single-image deblurring with neural networks: A comparative survey
- Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding
- Deep Robust Image Deblurring via Blur Distilling and Information Comparison in Latent Space
- Deep Image Deblurring: A Survey
- Deep Feature Prior Guided Face Deblurring
- Restormer: Efficient transformer for high-resolution image restoration
- Maxim: Multi-axis mlp for image processing - research/maxim)|
- Uformer: A general u-shaped transformer for image restoration
- Deblurring via Stochastic Refinement
- XYDeblur: Divide and Conquer for Single Image Deblurring
- All-In-One Image Restoration for Unknown Corruption - SCU/2022-CVPR-AirNet)|
- Exploring and Evaluating Image Restoration Potential in Dynamic Scenes
- Deep Generalized Unfolding Networks for Image Restoration - E/Deep-Generalized-Unfolding-Networks-for-Image-Restoration)|
- GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation
- Blind Non-Uniform Motion Deblurring Using Atrous Spatial Pyramid Deformable Convolution and Deblurring-Reblurring Consistency
- Motion Aware Double Attention Network for Dynamic Scene Deblurring
- Stripformer: Strip Transformer for Fast Image Deblurring
- Simple baselines for image restoration - research/NAFNet)|
- D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration
- Learning Degradation Representations for Image Deblurring
- Realistic Blur Synthesis for Learning Image Deblurring
- Event-based Fusion for Motion Deblurring with Cross-modal Attention
- Multi-scale-stage network for single image deblurring
- Intriguing Findings of Frequency Selection for Image Deblurring - Lab-ECNU/DeepRFT-AAAI2023)|
- Dual-domain Attention for Image Deblurring
- Multiscale Structure Guided Diffusion for Image Deblurring
- Multi-Scale Residual Low-Pass Filter Network for Image Deblurring
- Blind Image Deconvolution using Deep Generative Priors
- Self-Supervised Non-Uniform Kernel Estimation With Flow-Based Motion Prior for Blind Image Deblurring
- Efficient Frequency Domain-Based Transformers for High-Quality Image Deblurring
- Self-Supervised Blind Motion Deblurring With Deep Expectation Maximization
- Learning to Predict Decomposed Dynamic Filters for Single Image Motion Deblurring
- Blind Image Deblurring with Unknown Kernel Size and Substantial Noise - umn/Blind-Image-Deblurring)|
- Learning to Deblur Face Images via Sketch Synthesis
-
Benchmark Datasets on Motion Deblurring
- Human-Aware Motion Deblurring
- Stereo Deblurring With View Aggregation
- Understanding and evaluating blind deconvolution algorithms
- Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database
- A Comparative Study for Single Image Blind Deblurring
- Motion deblurring in the wild
- Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring - tech/ESTRNN)|
- Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms
- MC-Blur: A Comprehensive Benchmark for Image Deblurring - Blur-Dataset)||
- Edge-based blur kernel estimation using patch priors
- Deblurring by Realistic Blurring - by-Realistic-Blurring)|
- Realistic Blur Synthesis for Learning Image Deblurring
- Edge-based blur kernel estimation using patch priors
- Learning Event-Based Motion Deblurring
- Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes - tech/RSCD)||
- Real-world deep local motion deblurring
- Deep multi-scale convolutional neural network for dynamic scene deblurring
- Blur Interpolation Transformer for Real-World Motion from Blur - tech/BiT)|
- Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Network - tech/ESTRNN)|
-
Defocus Deblurring and Potential Datasets
- Single image defocus map estimation using local contrast prior
- What are Good Apertures for Defocus Deblurring?
- Defocus map estimation from a single image
- Spatially-varying out-of-focus image deblurring with L1-2 optimization and a guided blur map
- Removing out-of-focus blur from similar image pairs
- Discriminative Blur Detection Features
- Just Noticeable Defocus Blur Detection and Estimation
- Spatially Variant Defocus Blur Map Estimation and Deblurring from a Single Image - deblurring)|
- Depth Estimation and Blur Removal from a Single Out-of-focus Image
- Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes
- A unified approach of multi-scale deep and hand-crafted features for defocus estimation
- Learning to Synthesize a 4D RGBD Light Field from a Single Image
- Refocusgan: Scene refocusing using a single image
- Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?
- Defocus and Motion Blur Detection with Deep Contextual Features
- Edge-based defocus blur estimation with adaptive scale selection - Edge-Based-Defocus-Blur-Estimation-With-Adaptive-Scale-Selection)|
- Deep Defocus Map Estimation using Domain Adaptation
- DeFusionNET: Defocus Blur Detection via Recurrently Fusing and Refining Multi-Scale Deep Features
- Defocus Deblurring Using Dual-Pixel Data - Abuolaim/defocus-deblurring-dual-pixel)|
- Rethinking the Defocus Blur Detection Problem and A Real-Time Deep DBD Model
- Defocus Blur Detection via Depth Distillation - distillation)|
- AIFNet: All-in-focus Image Restoration Network using a Light Field-based Dataset
- CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry
- Deep Multi-Scale Feature Learning for Defocus Blur Estimation
- Estimating Generalized Gaussian Blur Kernels for Out-of-Focus Image Deblurring
- Defocus Blur Detection via Salient Region Detection Prior
- Learning to Estimate Kernel Scale and Orientation of Defocus Blur with Asymmetric Coded Aperture
- Iterative Filter Adaptive Network for Single Image Defocus Deblurring
- Self-Generated Defocus Blur Detection via Dual Adversarial Discriminators
- Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration - Pixel-Exploration-Simultaneous-Depth-Estimation-and-Image-Restoration)|
- NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results
- Attention! Stay Focus!
- Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions
- Learning To Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data - Abuolaim/recurrent-defocus-deblurring-synth-dual-pixel)|
- Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning - Abuolaim/multi-task-defocus-deblurring-dual-pixel-nimat)|
- Learning to Deblur Using Light Field Generated and Real Defocus Images
- AR-NeRF: Unsupervised Learning of Depth and Defocus Effects From Natural Images With Aperture Rendering Neural Radiance Fields
- United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning
- Learning Single Image Defocus Deblurring with Misaligned Training Pairs
- Single Image Defocus Deblurring via Implicit Neural Inverse Kernels
- Camera-Independent Single Image Depth Estimation From Defocus Blur
- K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring
- Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution
- Neumann Network With Recursive Kernels for Single Image Defocus Deblurring
- DP-NeRF: Deblurred Neural Radiance Field With Physical Scene Priors
- End-to-end Alternating Optimization for Real-World Blind Super Resolution
- LaKDNet: Revisiting Image Deblurring with an Efficient ConvNet
-
Other Closely Related Works
- Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions
- Event-Guided Deblurring of Unknown Exposure Time Videos
- Multiframe Restoration Methods for Image Synthesis and Recovery, Joseph J. Green, Univ. of Arizona, PhD thesis - jpl/pmapper)|
- A No-Reference Metric for Evaluating The Quality of Motion Deblurring
- Learning to extract a video sequence from a single motion-blurred image - to-Extract-a-Video-Sequence-from-a-Single-Motion-Blurred-Image)|
- Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera - a-Blurry-Frame-Alive-at-High-Frame-Rate-with-an-Event-Camera)|
- Learning to Extract Flawless Slow Motion From Blurry Videos - motion)|
- Learning to Synthesize Motion Blur - research/google-research/tree/master/motion_blur), [Project page](http://timothybrooks.com/tech/motion-blur/)|
- World from blur
- FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos
- Photosequencing of Motion Blur using Short and Long Exposures
- Watch out! Motion is Blurring Blurring the Vision of Your Deep Neural Networks
- Geometric Moment Invariants to Motion Blur
- Optical Flow Estimation from a Single Motion-blurred Image
- Improved Handling of Motion Blur in Online Object Detection
- Blur, Noise, and Compression Robust Generative Adversarial Networks
- Motion Deblurring With Real Events - Deblurring-with-Real-Events)|
- Bringing Events Into Video Deblurring With Non-Consecutively Blurry Frames
- Non-Coaxial Event-Guided Motion Deblurring with Spatial Alignment
- Generalizing Event-Based Motion Deblurring in Real-World Scenarios - 0/GEM)|
- Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects with Denoising Diffusion Probabilistic Models - DDPM-FMO)|
- Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance - tech/Animation-from-Blur)|
- Robust Single Image Deblurring Using Gyroscope Sensor
- Improving Robustness of Semantic Segmentation to Motion-Blur Using Class-Centric Augmentation - discover/CCMBA_CVPR23)|
- 2023
- Blur Interpolation Transformer for Real-World Motion from Blur - tech/BiT?tab=readme-ov-file)|
- Event-Based Frame Interpolation with Ad-hoc Deblurring
- DartBlur: Privacy Preservation With Detection Artifact Suppression
- HyperCUT: Video Sequence From a Single Blurry Image Using Unsupervised Ordering
- Hybrid Neural Rendering for Large-Scale Scenes With Motion Blur - Rendering-ProjectPage)|
- Event-Based Blurry Frame Interpolation Under Blind Exposure - BE)|
-
Challenges on Motion Deblurring
- NTIRE 2019 Challenge on Video Deblurring: Methods and Results
- NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study
- EDVR: Video Restoration with Enhanced Deformable Convolutional Networks - Pytorch](https://github.com/xinntao/EDVR)|[Project page](https://xinntao.github.io/projects/EDVR)|
- Ntire 2020 challenge on image and video deblurring
- Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency
- High-Resolution Dual-Stage Multi-Level Feature Aggregation for Single Image and Video Deblurring
-
AI-Photo-Enhancer-Apps
Categories
Non-Blind-Deblurring
145
Single-Image-Blind-Motion-Deblurring (DL)
97
Single-Image-Blind-Motion-Deblurring (non-DL)
89
(Multi-image/Video)-Motion-Deblurring
64
Defocus Deblurring and Potential Datasets
47
Other Closely Related Works
31
Benchmark Datasets on Motion Deblurring
19
Challenges on Motion Deblurring
6
AI-Photo-Enhancer-Apps
1
Sub Categories