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 1111–1120 of 3874 papers

TitleStatusHype
Multigrid Backprojection Super-Resolution and Deep Filter VisualizationCode0
Multimodal Sensor Fusion In Single Thermal image Super-ResolutionCode0
MRI Super-Resolution using Multi-Channel Total VariationCode0
MR Slice Profile Estimation by Learning to Match Internal Patch DistributionsCode0
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural NetworksCode0
A Motion Assessment Method for Reference Stack Selection in Fetal Brain MRI Reconstruction Based on Tensor Rank ApproximationCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Binary Document Image Super Resolution for Improved Readability and OCR PerformanceCode0
Model-Guided Network with Cluster-Based Operators for Spatio-Spectral Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified