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 431–440 of 597 papers

TitleStatusHype
Experimental comparison of single-pixel imaging algorithms—0
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks—0
GPU-Accelerated Algorithms for Compressed Signals Recovery with Application to Astronomical Imagery Deblurring—0
ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive SensingCode0
Two-pixel polarimetric camera by compressive sensing—0
Measurement-Adaptive Sparse Image Sampling and Recovery—0
Nonconvex penalties with analytical solutions for one-bit compressive sensing—0
Image Compression Based on Compressive Sensing: End-to-End Comparison with JPEG—0
Image Restoration from Patch-based Compressed Sensing Measurement—0
Provable Dynamic Robust PCA or Robust Subspace TrackingCode0
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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