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 751–800 of 999 papers

TitleStatusHype
Prior-enlightened and Motion-robust Video Deblurring—0
Blind Image Deblurring: a Review—0
Unleashing the Power of Data Synthesis in Visual Localization—0
Blind Deconvolution Method using Omnidirectional Gabor Filter-based Edge Information—0
Blind Deblurring using Deep Learning: A Survey—0
Prompt-tuning latent diffusion models for inverse problems—0
Blind deblurring of hyperspectral document images—0
Prototype Clustered Diffusion Models for Versatile Inverse Problems—0
Unnatural L0 Sparse Representation for Natural Image Deblurring—0
Unpaired Deblurring via Decoupled Diffusion Model—0
Blind Deblurring for Saturated Images—0
Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration—0
Pyramid Architecture Search for Real-Time Image Deblurring—0
Pyramid Feature Alignment Network for Video Deblurring—0
QQATeam at Qur’an QA 2022: Fine-Tunning Arabic QA Models for Qur’an QA Task—0
Quad-Pixel Image Defocus Deblurring: A New Benchmark and Model—0
Quality Adaptive Low-Rank Based JPEG Decoding with Applications—0
Unsupervised Blind Image Deblurring Based on Self-Enhancement—0
Quaternion Nuclear Norm minus Frobenius Norm Minimization for color image reconstruction—0
Unsupervised Class-Specific Deblurring—0
Blind deblurring for microscopic pathology images using deep learning networks—0
Bi-Skip: A Motion Deblurring Network Using Self-paced Learning—0
Bi-l0-l2-Norm Regularization for Blind Motion Deblurring—0
Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network—0
Beyond Camera Motion Blur Removing: How to Handle Outliers in Deblurring—0
Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms—0
Real-World Deep Local Motion Deblurring—0
Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization—0
Real-world Instance-specific Image Goal Navigation: Bridging Domain Gaps via Contrastive Learning—0
Reblur2Deblur: Deblurring Videos via Self-Supervised Learning—0
Unsupervised Domain-Specific Deblurring using Scale-Specific Attention—0
Recent Progress in Image Deblurring—0
Reconstruct Anything Model: a lightweight foundation model for computational imaging—0
Recurrence-in-Recurrence Networks for Video Deblurring—0
Recurrent Neural Networks With Intra-Frame Iterations for Video Deblurring—0
Beam-Shape Effects and Noise Removal from THz Time-Domain Images in Reflection Geometry in the 0.25-6 THz Range—0
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie—0
Reference-based Motion Blur Removal: Learning to Utilize Sharpness in the Reference Image—0
Reference-Free Image Quality Metric for Degradation and Reconstruction Artifacts—0
Reflection Separation and Deblurring of Plenoptic Images—0
RefocusGAN: Scene Refocusing using a Single Image—0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Regularising Inverse Problems with Generative Machine Learning Models—0
Regularization by denoising: Bayesian model and Langevin-within-split Gibbs sampling—0
Regularization by Denoising via Fixed-Point Projection (RED-PRO)—0
Regularization via deep generative models: an analysis point of view—0
RELD: Regularization by Latent Diffusion Models for Image Restoration—0
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration—0
A Deep Variational Bayesian Framework for Blind Image Deblurring—0
Residual Expansion Algorithm: Fast and Effective Optimization for Nonconvex Least Squares Problems—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
7DeepRFT+PSNR (sRGB)31.66—Unverified
8ID-Blau (Restormer)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
10MPRNetPSNR (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