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 1121–1130 of 3874 papers

TitleStatusHype
MRI Super-Resolution using Multi-Channel Total VariationCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Deformable Non-local Network for Video Super-ResolutionCode0
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural NetworksCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Multi Kernel Estimation based Object SegmentationCode0
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion CompensationCode0
A Matrix-in-matrix Neural Network for Image Super ResolutionCode0
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification LayersCode0
Unsupervised Hyperspectral and Multispectral Image Fusion via Self-Supervised Modality DecouplingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified