SOTAVerified

Deblurring

Deblurring is a computer vision task that involves removing the blurring artifacts from images or videos to restore the original, sharp content. Blurring can be caused by various factors such as camera shake, fast motion, and out-of-focus objects, and can result in a loss of detail and quality in the captured images. The goal of deblurring is to produce a clear, high-quality image that accurately represents the original scene.

( Image credit: Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks )

Papers

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Showing 451–500 of 999 papers

TitleStatusHype
Blind Image Deblurring via Reweighted Graph Total Variation—0
Blind Image Deblurring With Local Maximum Gradient Prior—0
Blind Image Deblurring With Outlier Handling—0
Blind Image Super-Resolution with Spatial Context Hallucination—0
Blind Inversion using Latent Diffusion Priors—0
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
Blind Motion Deblurring through SinGAN Architecture—0
Blind Motion Deblurring with Cycle Generative Adversarial Networks—0
Blind restoration for non-uniform aerial images using non-local Retinex model and shearlet-based higher-order regularization—0
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems—0
Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains—0
Blur-Attention: A boosting mechanism for non-uniform blurred image restoration—0
Blur-Invariant Deep Learning for Blind-Deblurring—0
Blur Invariants for Image Recognition—0
Blur Kernel Estimation Using Normalized Color-Line Prior—0
Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring—0
Blur Processing Using Double Discrete Wavelet Transform—0
Boosting Image Restoration via Priors from Pre-trained Models—0
BP-DIP: A Backprojection based Deep Image Prior—0
Bregman Iteration for Correspondence Problems: A Study of Optical Flow—0
Burst Deblurring: Removing Camera Shake Through Fourier Burst Accumulation—0
Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks—0
CANDID: Correspondence AligNment for Deep-burst Image Denoising—0
Can We Boost the Power of the Viola-Jones Face Detector Using Pre-processing? An Empirical Study—0
Cascades of Regression Tree Fields for Image Restoration—0
Class-Specific Image Deblurring—0
Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurring—0
ClearSight: Human Vision-Inspired Solutions for Event-Based Motion Deblurring—0
CNN for License Plate Motion Deblurring—0
CodEx: A Modular Framework for Joint Temporal De-blurring and Tomographic Reconstruction—0
Coding-Prior Guided Diffusion Network for Video Deblurring—0
Collaborative Blind Image Deblurring—0
Collaborative Total Variation: A General Framework for Vectorial TV Models—0
Comparative Analysis of Non-Blind Deblurring Methods for Noisy Blurred Images—0
Complementary Sets of Shutter Sequences for Motion Deblurring—0
Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems—0
Constrained Diffusion Implicit Models—0
Continual Test-Time Adaptation for Single Image Defocus Deblurring via Causal Siamese Networks—0
Controlling Neural Networks via Energy Dissipation—0
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter—0
Convolutional Neural Networks Analyzed via Inverse Problem Theory and Sparse Representations—0
Convolutional Neural Networks Deceived by Visual Illusions—0
Convolutional Sparse Coding: Boundary Handling Revisited—0
CoordGate: Efficiently Computing Spatially-Varying Convolutions in Convolutional Neural Networks—0
Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems—0
DAP-LED: Learning Degradation-Aware Priors with CLIP for Joint Low-light Enhancement and Deblurring—0
DAVID: Dual-Attentional Video Deblurring—0
DAWN-FM: Data-Aware and Noise-Informed Flow Matching for Solving Inverse Problems—0
DC2: Dual-Camera Defocus Control by Learning To Refocus—0
Deblur Gaussian Splatting SLAM—0
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All datasetsGoProHIDE (trained on GOPRO)RealBlur-R (trained on GoPro)RealBlur-JRealBlur-RRealBlur-J (trained on GoPro)RSBlurMSU BASEDDVDBeam-Splitter Deblurring (BSD)BASEDREDS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BSSTNetPSNR35.98—Unverified
2GShift-NetPSNR35.88—Unverified
3DLEFNetPSNR35.61—Unverified
4EFNetPSNR35.46—Unverified
5NIREPSNR35.03—Unverified
6VRTPSNR34.81—Unverified
7AdaRevDPSNR34.6—Unverified
8TurtlePSNR34.5—Unverified
9ID-Blau (FFTformer)PSNR34.36—Unverified
10XYScanNetPSNR33.91—Unverified
#ModelMetricClaimedVerifiedStatus
1MAXIMPSNR (sRGB)32.83—Unverified
2AdaRevDPSNR (sRGB)32.35—Unverified
3ID-Blau (FFTformer)PSNR (sRGB)31.94—Unverified
4LoFormerPSNR (sRGB)31.86—Unverified
5CAPTNetPSNR (sRGB)31.86—Unverified
6XYScanNetPSNR (sRGB)31.74—Unverified
7ID-Blau (Restormer)PSNR (sRGB)31.66—Unverified
8DeepRFT+PSNR (sRGB)31.66—Unverified
9FFTformerPSNR (sRGB)31.62—Unverified
10LaKDNetPSNR (sRGB)31.58—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaRevDPSNR (sRGB)36.53—Unverified
2ALGNetPSNR (sRGB)36.35—Unverified
3Uformer-BPSNR (sRGB)36.22—Unverified
4RestormerPSNR (sRGB)36.19—Unverified
5DeepRFTPSNR (sRGB)36.11—Unverified
6DeblurDiNAT-LPSNR (sRGB)36.09—Unverified
7LaKDNetPSNR (sRGB)36.08—Unverified
8MPRNetPSNR (sRGB)35.99—Unverified
9MSSNetPSNR (sRGB)35.93—Unverified
10MAXIMPSNR (sRGB)35.78—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaRevDPSNR (sRGB)33.96—Unverified
2MLWNetPSNR (sRGB)33.84—Unverified
3ID-Blau (Stripformer)PSNR (sRGB)33.77—Unverified
4ID-Blau (Restormer)PSNR (sRGB)33.11—Unverified
5ALGNetPSNR (sRGB)32.94—Unverified
6LoFormerPSNR (sRGB)32.9—Unverified
7ID-Blau (FFTformer)PSNR (sRGB)32.88—Unverified
8MAXIMPSNR (sRGB)32.84—Unverified
9DeepRFT+PSNR (sRGB)32.63—Unverified
10FFTformerPSNR (sRGB)32.62—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaRevDPSNR (sRGB)41.19—Unverified
2ALGNetPSNR (sRGB)41.16—Unverified
3ID-Blau (Stripformer)PSNR (sRGB)41.06—Unverified
4MLWNetPSNR (sRGB)40.69—Unverified
5ID-Blau (FFTformer)PSNR (sRGB)40.45—Unverified
6ID-Blau (Restormer)PSNR (sRGB)40.31—Unverified
7LoFormerPSNR (sRGB)40.23—Unverified
8FFTformerPSNR (sRGB)40.11—Unverified
9DeepRFT+PSNR (sRGB)40.01—Unverified
10StripformerPSNR (sRGB)39.84—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaRevDPSNR (sRGB)30.12—Unverified
2UFPNetPSNR (sRGB)29.87—Unverified
3ALGNetPSNR (sRGB)29.12—Unverified
4Uformer-BPSNR (sRGB)29.06—Unverified
5DeblurDiNAT-LPSNR (sRGB)28.98—Unverified
6RestormerPSNR (sRGB)28.96—Unverified
7DeepRFT+PSNR (sRGB)28.88—Unverified
8MAXIMPSNR (sRGB)28.83—Unverified
9MSSNetPSNR (sRGB)28.79—Unverified
10DeblurGAN-v2PSNR (sRGB)28.7—Unverified
#ModelMetricClaimedVerifiedStatus
1MLWNetAverage PSNR34.94—Unverified
2SegDeblurAverage PSNR34.63—Unverified
3SFNetAverage PSNR34.35—Unverified
4FSNetAverage PSNR34.31—Unverified
5IRNextAverage PSNR34.08—Unverified
6ConvIRAverage PSNR34.06—Unverified
7Uformer-BAverage PSNR33.98—Unverified
8RestormerAverage PSNR33.69—Unverified
9MPRNetAverage PSNR33.61—Unverified
10MIMO-UNet+Average PSNR33.37—Unverified
#ModelMetricClaimedVerifiedStatus
1NAFNet (REDS)Subjective2.84—Unverified
2VRT (GoPro)Subjective2.39—Unverified
3VRT (REDS)Subjective1.57—Unverified
4DeblurGAN InceptionSubjective1.04—Unverified
5MAXIM (REDS)Subjective1.01—Unverified
6Deeprft (GoPro)Subjective0.54—Unverified
7Deeprft (REDS)Subjective0.46—Unverified
8MPR localSubjective0.44—Unverified
9MAXIM (GoPro)Subjective0.21—Unverified
10Restormer localSubjective0.12—Unverified
#ModelMetricClaimedVerifiedStatus
1BSSTNetPSNR34.95—Unverified
2RVRTPSNR34.92—Unverified
3GShift-NetPSNR34.69—Unverified
4VRTPSNR34.27—Unverified
5FGSTPSNR33.5—Unverified
6STDANPSNR33.05—Unverified
7FGSTPSNR33.03—Unverified
8MB2DPSNR32.34—Unverified
9CDVD-TSPPSNR32.13—Unverified
10STFANPSNR31.27—Unverified
#ModelMetricClaimedVerifiedStatus
1TurtlePSNR33.58—Unverified
2CDVD-TSPPSNR31.58—Unverified
3ESTRNNPSNR31.39—Unverified
4PVDNetPSNR31.35—Unverified
5DBNPSNR31.21—Unverified
#ModelMetricClaimedVerifiedStatus
1VRT (GoPro)PSNR31.43—Unverified
2DeblurGAN InceptionPSNR31.17—Unverified
3VRT (REDS)PSNR30.98—Unverified
4MAXIM (REDS)PSNR30.66—Unverified
#ModelMetricClaimedVerifiedStatus
1VRTAverage PSNR36.79—Unverified
2EDVR_DeblurAverage PSNR34.8—Unverified
3DeblurGANAverage PSNR24.09—Unverified
#ModelMetricClaimedVerifiedStatus
1MIMO-UNet + Realistic blurAverage PSNR32.08—Unverified
2SRN-Deblur + Realistic blurAverage PSNR32.06—Unverified
#ModelMetricClaimedVerifiedStatus
1110 Images, 4*4 Stitching, Exact Accuracy2—Unverified
#ModelMetricClaimedVerifiedStatus
1MAXIM-3SPSNR32.83—Unverified
#ModelMetricClaimedVerifiedStatus
1OursMAE0.04—Unverified