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 101–125 of 597 papers

TitleStatusHype
An Efficient Method for Robust Projection Matrix DesignCode0
Modeling and Optimization for Flexible Cylindrical Arrays-Enabled Wireless CommunicationsCode0
Deep Unfolding Basis Pursuit: Improving Sparse Channel Reconstruction via Data-Driven Measurement MatricesCode0
Multi-Scale Deep Compressive Sensing NetworkCode0
A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse ProblemsCode0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive ImagingCode0
Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid PrecodingCode0
One Network to Solve Them All -- Solving Linear Inverse Problems Using Deep Projection ModelsCode0
Online Learning Sensing Matrix and Sparsifying Dictionary Simultaneously for Compressive SensingCode0
Fast L1-Minimization Algorithms For Robust Face RecognitionCode0
Deep Decomposition Learning for Inverse Imaging ProblemsCode0
Compressive Image Scanning MicroscopeCode0
CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive SensingCode0
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial NetworksCode0
DeepBinaryMask: Learning a Binary Mask for Video Compressive SensingCode0
Deep Fully-Connected Networks for Video Compressive SensingCode0
Bayesian Sparse Tucker Models for Dimension Reduction and Tensor CompletionCode0
Covariance Estimation from Compressive Data Partitions using a Projected Gradient-based AlgorithmCode0
Deep Geometric Distillation Network for Compressive Sensing MRICode0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and ThresholdsCode0
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive VideoCode0
Machine Learning Assisted Phase-less Millimeter-Wave Beam Alignment in Multipath ChannelsCode0
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI—0
Compressive sensing adaptation for polynomial chaos expansions—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