Blind Super-Resolution
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Benchmarks
DIV2KRK - 4x upscaling
DIV2KRK - 2x upscaling
BSD100 - 2x upscaling
BSD100 - 4x upscaling
Manga109 - 2x upscaling
Manga109 - 4x upscaling
Set14 - 2x upscaling
Set14 - 4x upscaling
Set5 - 2x upscaling
Set5 - 4x upscaling
Urban100 - 2x upscaling
Urban100 - 4x upscaling
BSD100 - 3x upscaling
Manga109 - 3x upscaling
Set14 - 3x upscaling
Set5 - 3x upscaling
Urban100 - 3x upscaling
DRealSR
Most implemented
Blind Super-Resolution Kernel Estimation using an Internal-GAN
Exploiting Diffusion Prior for Real-World Image Super-Resolution
Blind Super-Resolution With Iterative Kernel Correction
Boosting Diffusion Guidance via Learning Degradation-Aware Models for Blind Super Resolution
End-to-end Alternating Optimization for Real-World Blind Super Resolution
Papers
Interest Entanglement: The Hidden Barrier to Blind Super-Resolution Optimization
Fidelity and perceptual quality are two inherently competing and conflicting objectives in the image super-resolution (SR) task. Different loss functions focus on these objectives to varying extents. Regression losses en…
Dimensionality ReductionImage Super-ResolutionBlind Super-ResolutionMultispectral Blind Image Super-Resolution for Standing Dead Tree Segmentation
Mapping standing dead trees is crucial for acquiring information on the effects of climate change on forests and forest biodiversity. However, leveraging high-quality aerial imagery for dead tree segmentation poses chall…
Image Super-ResolutionBlind Super-ResolutionDomain AdaptationHistory-Augmented Contrastive Learning With Soft Mixture of Experts for Blind Super-Resolution of Planetary Remote Sensing Images
Blind Super-Resolution (BSR) in planetary remote sensing constitutes a highly ill-posed inverse problem, characterized by unknown degradation patterns and a complete absence of ground-truth supervision. Existing unsuperv…
Blind Super-ResolutionImage ReconstructionContrastive LearningTwo Heads Better than One: Dual Degradation Representation for Blind Super-Resolution
Previous methods have demonstrated remarkable performance in single image super-resolution (SISR) tasks with known and fixed degradation (e.g., bicubic downsampling). However, when the actual degradation deviates from th…
Image Super-ResolutionBlind Super-ResolutionBlind Super Resolution with Reference Images and Implicit Degradation Representation
Previous studies in blind super-resolution (BSR) have primarily concentrated on estimating degradation kernels directly from low-resolution (LR) inputs to enhance super-resolution. However, these degradation kernels, whi…
Blind Super-ResolutionUnsupervised Imaging Inverse Problems with Diffusion Distribution Matching
This work addresses image restoration tasks through the lens of inverse problems using unpaired datasets. In contrast to traditional approaches -- which typically assume full knowledge of the forward model or access to p…
Blind Super-ResolutionDeblurringImage RestorationSuper-Resolution