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 1831–1840 of 3874 papers

TitleStatusHype
Improving Multi-View Stereo via Super-Resolution—0
Improving Object Detection Quality in Football Through Super-Resolution Techniques—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
A mathematical theory of resolution limits for super-resolution of positive sources—0
Joint Super-Resolution and Rectification for Solar Cell Inspection—0
FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization—0
Improving the resolution of microscope by deconvolution after dense scan—0
Context Reasoning Attention Network for Image Super-Resolution—0
FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution—0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified