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 101–150 of 597 papers

TitleStatusHype
An Efficient Method for Robust Projection Matrix DesignCode0
Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural NetworkCode0
Difference of Convolution for Deep Compressive SensingCode0
Sparse Depth Sensing for Resource-Constrained RobotsCode0
Towards improving discriminative reconstruction via simultaneous dense and sparse codingCode0
Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid PrecodingCode0
Deep Geometric Distillation Network for Compressive Sensing MRICode0
Towards Real-time Video Compressive Sensing on Mobile DevicesCode0
Training Image Estimators without Image Ground-TruthCode0
Training Image Estimators without Image Ground TruthCode0
Deep Decomposition Learning for Inverse Imaging ProblemsCode0
Deep Regularized Compound Gaussian Network for Solving Linear Inverse ProblemsCode0
CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive SensingCode0
Covariance Estimation from Compressive Data Partitions using a Projected Gradient-based AlgorithmCode0
DeepBinaryMask: Learning a Binary Mask for Video Compressive SensingCode0
A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse ProblemsCode0
Full Image Recover for Block-Based Compressive SensingCode0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
Machine Learning Assisted Phase-less Millimeter-Wave Beam Alignment in Multipath ChannelsCode0
Recursions Are All You Need: Towards Efficient Deep Unfolding NetworksCode0
Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems—0
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI—0
Compressive sensing adaptation for polynomial chaos expansions—0
Compressive Scanning Transmission Electron Microscopy—0
A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy—0
Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences—0
A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames—0
Compressive radio-interferometric sensing with random beamforming as rank-one signal covariance projections—0
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Asynchronous Multi Agent Active Search—0
Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors—0
Compressive phase-only filtering at extreme compression rates—0
A Survey: Non-Orthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC—0
A fast patch-dictionary method for whole image recovery—0
Active Search for Sparse Signals with Region Sensing—0
Compressive Pattern Matching on Multispectral Data—0
Compressive neural representation of sparse, high-dimensional probabilities—0
Compressive Measurement Designs for Estimating Structured Signals in Structured Clutter: A Bayesian Experimental Design Approach—0
Compressively Sensed Image Recognition—0
A Parallel Compressive Imaging Architecture for One-Shot Acquisition—0
A Fast Noniterative Algorithm for Compressive Sensing Using Binary Measurement Matrices—0
Compressive Light Field Reconstructions using Deep Learning—0
Compressive lensless endoscopy with partial speckle scanning—0
A Novel Radar Constant False Alarm Rate Detection Algorithm Based on VAMP Deep Unfolding—0
Compressive Hyperspectral Imaging with Side Information—0
A Nonlinear Weighted Total Variation Image Reconstruction Algorithm for Electrical Capacitance Tomography—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
Compressive hyperspectral imaging via adaptive sampling and dictionary learning—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