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 391–400 of 597 papers

TitleStatusHype
Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior—0
Depth and Transient Imaging With Compressive SPAD Array Cameras—0
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI—0
Frequency-modulated continuous-wave LiDAR compressive depth-mapping—0
Active User Detection of Uplink Grant-Free SCMA in Frequency Selective Channel—0
Compressive Sensing Imaging of 3-D Object by a Holographic Algorithm—0
Estimation with Low-Rank Time-Frequency Synthesis Models—0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Kinetic Compressive Sensing—0
Generalized Optimization of High Capacity Compressive Imaging Systems—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