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 3771–3780 of 3874 papers

TitleStatusHype
Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture SynthesisCode0
Generalized super-resolution 4D Flow MRI x2013 using ensemble learning to extend across the cardiovascular systemCode0
Gated Multiple Feedback Network for Image Super-ResolutionCode0
Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment TechnologyCode0
Gated Fusion Network for Joint Image Deblurring and Super-ResolutionCode0
Game Theory for Adversarial Attacks and DefensesCode0
RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid SubjectsCode0
Audio Super Resolution using Neural NetworksCode0
xUnit: Learning a Spatial Activation Function for Efficient Image RestorationCode0
GAMBAS: Generalised-Hilbert Mamba for Super-resolution of Paediatric Ultra-Low-Field MRICode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified