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 2201–2210 of 3874 papers

TitleStatusHype
FFT-Enhanced Low-Complexity Near-Field Super-Resolution Sensing—0
FFTLasso: Large-Scale LASSO in the Fourier Domain—0
Fidelity-Naturalness Evaluation of Single Image Super Resolution—0
Fine-Grained Neural Architecture Search—0
Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain—0
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution—0
Fingerprinting Deep Image Restoration Models—0
Fingerprints of Super Resolution Networks—0
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models—0
FireSRnet: Geoscience-Driven Super-Resolution of Future Fire Risk from Climate Change—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified