SOTAVerified

Compressive Sensing

Compressive Sensing is a new signal processing framework for efficiently acquiring and reconstructing a signal that have a sparse representation in a fixed linear basis.

Source: Sparse Estimation with Generalized Beta Mixture and the Horseshoe Prior

Papers

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Showing 551–560 of 597 papers

TitleStatusHype
Fast L1-Minimization Algorithms For Robust Face RecognitionCode0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection ModelsCode0
Modeling and Optimization for Flexible Cylindrical Arrays-Enabled Wireless CommunicationsCode0
Deep Regularized Compound Gaussian Network for Solving Linear Inverse ProblemsCode0
ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive SensingCode0
One Network to Solve Them All -- Solving Linear Inverse Problems Using Deep Projection ModelsCode0
One-Shot Neural Architecture Search via Compressive SensingCode0
SUREMap: Predicting Uncertainty in CNN-based Image Reconstruction Using Stein's Unbiased Risk EstimateCode0
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All datasetsSet11 cs=50%BSD68 CS=50%BSDS100 - 2x upscalingUrban100 - 2x upscaling

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DMP-DUN-Plus (4-step)Average PSNR42.82—Unverified
2AMPA-NetAverage PSNR40.32—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR36.33—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.95—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.86—Unverified