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 1781–1790 of 3874 papers

TitleStatusHype
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
Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression—0
SGSR: Structure-Guided Multi-Contrast MRI Super-Resolution via Spatio-Frequency Co-Query Attention—0
DRCAS: Deep Restoration Network for Hardware Based Compressive Acquisition Scheme—0
Image Super-Resolution Using VDSR-ResNeXt and SRCGAN—0
Image Super-Resolution Using T-Tetromino Pixels—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified