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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
Blind Time-of-Flight Imaging: Sparse Deconvolution on the Continuum with Unknown Kernels—0
Content-decoupled Contrastive Learning-based Implicit Degradation Modeling for Blind Image Super-Resolution—0
Image Super-Resolution with Taylor Expansion Approximation and Large Field Reception—0
Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution—0
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
S2R: Exploring a Double-Win Transformer-Based Framework for Ideal and Blind Super-ResolutionCode0
Scale Guided Hypernetwork for Blind Super-Resolution Image Quality AssessmentCode0
Kernelized Back-Projection Networks for Blind Super Resolution—0
Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild—0
Self-FuseNet: Data Free Unsupervised Remote Sensing Image Super-Resolution—0
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