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 551–600 of 999 papers

TitleStatusHype
Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring—0
Dropout the High-rate Downsampling: A Novel Design Paradigm for UHD Image Restoration—0
Dual-Camera Joint Deblurring-Denoising—0
Dual Domain Filters Based Texture and Structure Preserving Image Non-Blind Deconvolution—0
DyBluRF: Dynamic Deblurring Neural Radiance Fields for Blurry Monocular Video—0
Dynamic Bandwidth Allocation for Hybrid Event-RGB Transmission—0
Dynamic Scene Deblurring Based on Continuous Cross-Layer Attention Transmission—0
Dynamic Scene Deblurring using a Locally Adaptive Linear Blur Model—0
Dynamic Scene Video Deblurring using Non-Local Attention—0
DynaMoDe-NeRF: Motion-aware Deblurring Neural Radiance Field for Dynamic Scenes—0
EaDeblur-GS: Event assisted 3D Deblur Reconstruction with Gaussian Splatting—0
EBAD-Gaussian: Event-driven Bundle Adjusted Deblur Gaussian Splatting—0
Edge Adaptive Hybrid Regularization Model For Image Deblurring—0
Edge-Aware Deep Image Deblurring—0
Edge-Based Blur Kernel Estimation Using Sparse Representation and Self-Similarity—0
Edge Heuristic GAN for Non-uniform Blind Deblurring—0
Edge Prior Augmented Networks for Motion Deblurring on Naturally Blurry Images—0
Efficient Dynamic Scene Deblurring Using Spatially Variant Deconvolution Network With Optical Flow Guided Training—0
Empirical Bayesian image restoration by Langevin sampling with a denoising diffusion implicit prior—0
Empowering Visually Impaired Individuals: A Novel Use of Apple Live Photos and Android Motion Photos—0
End-to-End Learning for Image Burst Deblurring—0
End-to-end Learning for Joint Depth and Image Reconstruction from Diffracted Rotation—0
Enhanced Fast Iterative Shrinkage Thresholding Algorithm For Linear Inverse Problem—0
Enhanced Sparse Model for Blind Deblurring—0
Enhancing Diffusion Models for Inverse Problems with Covariance-Aware Posterior Sampling—0
Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Enhancing Traffic Scene Predictions with Generative Adversarial Networks—0
EvaGaussians: Event Stream Assisted Gaussian Splatting from Blurry Images—0
Evaluating COPY-BLEND Augmentation for Low Level Vision Tasks—0
EventAid: Benchmarking Event-aided Image/Video Enhancement Algorithms with Real-captured Hybrid Dataset—0
Event-based Motion Deblurring via Multi-Temporal Granularity Fusion—0
Event-based Visible and Infrared Fusion via Multi-task Collaboration—0
Event-guided Deblurring of Unknown Exposure Time Videos—0
EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras—0
EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling—0
Explainable bilevel optimization: an application to the Helsinki deblur challenge—0
Exploring Temporal Frequency Spectrum in Deep Video Deblurring—0
ExpRDiff: Short-exposure Guided Diffusion Model for Realistic Local Motion Deblurring—0
Extreme Channel Prior Embedded Network for Dynamic Scene Deblurring—0
F2former: When Fractional Fourier Meets Deep Wiener Deconvolution and Selective Frequency Transformer for Image Deblurring—0
Face Deblurring Based on Separable Normalization and Adaptive Denormalization—0
Face Deblurring using Dual Camera Fusion on Mobile Phones—0
Face Recognition in Low Quality Images: A Survey—0
Face Video Deblurring Using 3D Facial Priors—0
Fast and easy blind deblurring using an inverse filter and PROBE—0
Fast and Full-Resolution Light Field Deblurring using a Deep Neural Network—0
Faster gradient descent and the efficient recovery of images—0
Fast Image Deconvolution using Hyper-Laplacian Priors—0
Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements—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