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 511–520 of 3874 papers

TitleStatusHype
3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstructionCode1
Deep Image PriorCode1
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
Deep Unfolding Network for Image Super-ResolutionCode1
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-ResolutionCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Deep Blind Video Super-resolutionCode1
Deep Burst Super-ResolutionCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified