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 3181–3190 of 3874 papers

TitleStatusHype
Super-resolved Localisation without Identifying LoS/NLoS Paths—0
Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution—0
Joint Super-Resolution and Alignment of Tiny FacesCode0
Fine-Grained Neural Architecture Search—0
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and ResultsCode0
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing—0
Frequency Separation for Real-World Super-ResolutionCode0
Towards the Automation of Deep Image Prior—0
Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair—0
Neutron Ghost Imaging—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified