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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 31–40 of 67 papers

TitleStatusHype
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net DiscriminatorsCode1
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIsCode1
End-to-end Alternating Optimization for Blind Super ResolutionCode1
Scale Guided Hypernetwork for Blind Super-Resolution Image Quality AssessmentCode0
Deep Fusion Prior for Plenoptic Super-Resolution All-in-Focus ImagingCode0
Boosting Diffusion Guidance via Learning Degradation-Aware Models for Blind Super ResolutionCode0
Blind Super-Resolution With Iterative Kernel CorrectionCode0
Blind Image Fusion for Hyperspectral Imaging with the Directional Total VariationCode0
Unsupervised Blur Kernel Estimation and Correction for Blind Super-ResolutionCode0
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