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 2051–2060 of 3874 papers

TitleStatusHype
Efficient and Phase-aware Video Super-resolution for Cardiac MRI—0
Efficient Channel Estimation for Millimeter Wave and Terahertz Systems Enabled by Integrated Super-resolution Sensing and Communication—0
Efficient Denoising Method to Improve The Resolution of Satellite Images—0
Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution—0
Efficient Hair Style Transfer with Generative Adversarial Networks—0
Efficient Hybrid Zoom using Camera Fusion on Mobile Phones—0
Efficient Image Super-Resolution via Symmetric Visual Attention Network—0
Efficient Learnable Collaborative Attention for Single Image Super-Resolution—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Efficient Medicinal Image Transmission and Resolution Enhancement via GAN—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified