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 3331–3340 of 3874 papers

TitleStatusHype
Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows—0
Super-Resolution and Image Re-projection for Iris Recognition—0
Super-Resolution and Sparse View CT Reconstruction—0
Super-Resolution Appearance Transfer for 4D Human Performances—0
AI-assisted super-resolution cosmological simulations—0
Super-Resolved Image Perceptual Quality Improvement via Multi-Feature Discriminators—0
Super Resolution Based on Deep Operator Networks—0
VIINTER: View Interpolation with Implicit Neural Representations of Images—0
Virtual Coil Augmentation Technology for MR Coil Extrapolation via Deep Learning—0
A Hybrid Registration and Fusion Method for Hyperspectral Super-resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified