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 1811–1820 of 3874 papers

TitleStatusHype
Image Transformer—0
IMDeception: Grouped Information Distilling Super-Resolution Network—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames—0
A comprehensive review on Plant Leaf Disease detection using Deep learning—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified