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Blind Super-Resolution

Blind Super-Resolution is an image processing technique that aims to reconstruct high-resolution images from low-resolution counterparts without prior knowledge of the degradation process.

Papers

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Showing 41–50 of 67 papers

TitleStatusHype
Unsupervised Blur Kernel Estimation and Correction for Blind Super-ResolutionCode0
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net DiscriminatorsCode1
Kernel-aware Burst Blind Super-ResolutionCode0
Pixel-Level Kernel Estimation for Blind Super-ResolutionCode0
Blind inverse problems with isolated spikes—0
Deep Fusion Prior for Plenoptic Super-Resolution All-in-Focus ImagingCode0
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Finding Discriminative Filters for Specific Degradations in Blind Super-ResolutionCode1
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