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 611–620 of 3874 papers

TitleStatusHype
Deep Random Projector: Accelerated Deep Image PriorCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Collaborative Feedback Discriminative Propagation for Video Super-ResolutionCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
A Practical Contrastive Learning Framework for Single-Image Super-ResolutionCode1
Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient ConvolutionCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified