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 561–570 of 597 papers

TitleStatusHype
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive VideoCode0
A Parallel Compressive Imaging Architecture for One-Shot Acquisition—0
Parameterless Optimal Approximate Message Passing—0
Compressed Sensing SAR Imaging with Multilook Processing—0
Optimal Sensor Placement and Enhanced Sparsity for Classification—0
Energy-aware adaptive bi-Lipschitz embeddings—0
On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements—0
Multi-view in Lensless Compressive Imaging—0
Robust Canonical Time Warping for the Alignment of Grossly Corrupted Sequences—0
Lensless Imaging by Compressive Sensing—0
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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