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 401–410 of 3874 papers

TitleStatusHype
One-stage Low-resolution Text Recognition with High-resolution Knowledge TransferCode1
Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-ResolutionCode1
Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point CloudsCode1
Lightweight Super-Resolution Head for Human Pose EstimationCode1
Fully 11 Convolutional Network for Lightweight Image Super-ResolutionCode1
StarSRGAN: Improving Real-World Blind Super-ResolutionCode1
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolutionCode1
On the Effectiveness of Spectral Discriminators for Perceptual Quality ImprovementCode1
Towards Robust Scene Text Image Super-resolution via Explicit Location EnhancementCode1
Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified