SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 481–490 of 3874 papers

TitleStatusHype
ADASR: An Adversarial Auto-Augmentation Framework for Hyperspectral and Multispectral Data FusionCode1
HQ-50K: A Large-scale, High-quality Dataset for Image RestorationCode1
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face RecognitionCode1
Deep Image PriorCode1
Physics Driven Deep Retinex Fusion for Adaptive Infrared and Visible Image FusionCode1
HST: Hierarchical Swin Transformer for Compressed Image Super-resolutionCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual LearningCode1
Hyperspectral Image Super-Resolution with Spectral Mixup and Heterogeneous DatasetsCode1
Deep Blind Super-Resolution for Satellite VideoCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified