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 2761–2770 of 3874 papers

TitleStatusHype
VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data—0
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery—0
Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound—0
AI-assisted super-resolution cosmological simulations—0
LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis—0
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions—0
Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 NetworkCode1
Diagnosing and Preventing Instabilities in Recurrent Video Processing—0
Attaining Real-Time Super-Resolution for Microscopic Images Using GANCode1
WDN: A Wide and Deep Network to Divide-and-Conquer Image Super-resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified