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 891–900 of 3874 papers

TitleStatusHype
Learning to Super-Resolve Blurry Images with EventsCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Lesion Focused Super-ResolutionCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
Lightweight Image Super-Resolution with Information Multi-distillation NetworkCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
Deep Unfolding Network for Image Super-ResolutionCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified