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 1221–1230 of 3874 papers

TitleStatusHype
Fidelity-Naturalness Evaluation of Single Image Super Resolution—0
Deep Residual Axial Networks—0
Beyond Pretty Pictures: Combined Single- and Multi-Image Super-resolution for Sentinel-2 Images—0
DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement—0
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey—0
Beyond MR Image Harmonization: Resolution Matters Too—0
Deep priors for satellite image restoration with accurate uncertainties—0
All-in-One Deep Learning Framework for MR Image Reconstruction—0
Adaptive Selection of Sampling-Reconstruction in Fourier Compressed Sensing—0
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified