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 2991–3000 of 3874 papers

TitleStatusHype
Volumetric Image Projection Super-Resolution Ultrasound (VIP-SR) with a 1D Unfocused Linear Array—0
Volumetric Super-Resolution of Multispectral Data—0
VoLUT: Efficient Volumetric streaming enhanced by LUT-based super-resolution—0
VSpSR: Explorable Super-Resolution via Variational Sparse Representation—0
Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models—0
WaveDiffUR: A diffusion SDE-based solver for ultra magnification super-resolution in remote sensing images—0
Wavelet-Based Segmentation on the Sphere—0
Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution—0
Wave-U-Mamba: An End-To-End Framework For High-Quality And Efficient Speech Super Resolution—0
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