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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 597 papers

TitleStatusHype
Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive SensingCode1
Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image RepresentationsCode1
MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive SensingCode1
Memory-Augmented Deep Unfolding Network for Compressive SensingCode1
AMPA-Net: Optimization-Inspired Attention Neural Network for Deep Compressed SensingCode1
A Spatially Separable Attention Mechanism for massive MIMO CSI FeedbackCode1
COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive SensingCode1
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximationCode1
CPP-Net: Embracing Multi-Scale Feature Fusion into Deep Unfolding CP-PPA Network for Compressive SensingCode1
D3C2-Net: Dual-Domain Deep Convolutional Coding Network for Compressive SensingCode1
Deep Compressive Offloading: Speeding Up Neural Network Inference by Trading Edge Computation for Network LatencyCode1
Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image ReconstructionCode1
Dynamic Path-Controllable Deep Unfolding Network for Compressive SensingCode1
A Low-Complexity MIMO Channel Estimator with Implicit Structure of a Convolutional Neural NetworkCode1
A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames—0
A fast patch-dictionary method for whole image recovery—0
Active Search for Sparse Signals with Region Sensing—0
A Fast Noniterative Algorithm for Compressive Sensing Using Binary Measurement Matrices—0
A Fast Alternating Minimization Algorithm for Coded Aperture Snapshot Spectral Imaging Based on Sparsity and Deep Image Priors—0
Across-domains transferability of Deep-RED in de-noising and compressive sensing recovery of seismic data—0
A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction—0
A Fast Algorithm for Low Rank + Sparse column-wise Compressive Sensing—0
ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI—0
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation—0
A Deep Learning Approach to Structured Signal Recovery—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