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

Showing 110 of 999 papers

TitleStatusHype
Generative Latent Kernel Modeling for Blind Motion DeblurringCode0
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
Dynamic Bandwidth Allocation for Hybrid Event-RGB Transmission0
Visual-Instructed Degradation Diffusion for All-in-One Image RestorationCode1
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level VisionCode1
Unsupervised Imaging Inverse Problems with Diffusion Distribution MatchingCode1
Restoring Gaussian Blurred Face Images for Deanonymization Attacks0
Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration ModelsCode0
Multi-Step Guided Diffusion for Image Restoration on Edge Devices: Toward Lightweight Perception in Embodied AI0
EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BSSTNetPSNR35.98Unverified
2GShift-NetPSNR35.88Unverified
3DLEFNetPSNR35.61Unverified
4EFNetPSNR35.46Unverified
5NIREPSNR35.03Unverified
6VRTPSNR34.81Unverified
7AdaRevDPSNR34.6Unverified
8TurtlePSNR34.5Unverified
9ID-Blau (FFTformer)PSNR34.36Unverified
10XYScanNetPSNR33.91Unverified