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
Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed SensingCode1
Ensemble learning priors unfolding for scalable Snapshot Compressive SensingCode1
Optimization-Inspired Cross-Attention Transformer for Compressive SensingCode1
Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting SurfacesCode1
AMPA-Net: Optimization-Inspired Attention Neural Network for Deep Compressed SensingCode1
Memory-Efficient Network for Large-scale Video Compressive SensingCode1
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive ImagingCode1
COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive SensingCode1
HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive ImagingCode1
Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximationCode1
CPP-Net: Embracing Multi-Scale Feature Fusion into Deep Unfolding CP-PPA Network for Compressive SensingCode1
SNIPS: Solving Noisy Inverse Problems StochasticallyCode1
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximationCode1
A Low-Complexity MIMO Channel Estimator with Implicit Structure of a Convolutional Neural NetworkCode1
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
Finer Metagenomic Reconstruction via Biodiversity OptimizationCode0
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent VariablesCode0
Fast L1-Minimization Algorithms For Robust Face RecognitionCode0
Flexible Intelligent Metasurface-Aided Wireless Communications: Architecture and PerformanceCode0
DR2-Net: Deep Residual Reconstruction Network for Image Compressive SensingCode0
Deep Unfolding Basis Pursuit: Improving Sparse Channel Reconstruction via Data-Driven Measurement MatricesCode0
Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural NetworkCode0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid PrecodingCode0
Show:102550
← PrevPage 2 of 24Next →
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