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 3321–3330 of 3874 papers

TitleStatusHype
Super Resolution for Root ImagingCode0
The World of Fast Moving ObjectsCode0
Non-Local Recurrent Network for Image RestorationCode0
Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity CluesCode0
Multi-scale deep neural networks for real image super-resolutionCode0
Super-resolution GANs of randomly-seeded fieldsCode0
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of MarsCode0
Three-Dimensional, Multimodal Synchrotron Data for Machine Learning ApplicationsCode0
A Multi-Pass GAN for Fluid Flow Super-ResolutionCode0
Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging SystemsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified