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 2771–2780 of 3874 papers

TitleStatusHype
Content-adaptive Representation Learning for Fast Image Super-resolution—0
XCycles Backprojection Acoustic Super-Resolution—0
Improved detection of small objects in road network sequences—0
Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement—0
Automated Symbolic Law Discovery: A Computer Vision Approach—0
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report—0
Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer—0
Capsule GAN for Prostate MRI Super-Resolution—0
Multi-scale super-resolution generation of low-resolution scanned pathological imagesCode0
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified