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 551–597 of 597 papers

TitleStatusHype
Video Compressive Sensing for Dynamic MRI—0
Multiscale Shrinkage and Lévy Processes—0
Binary Linear Classification and Feature Selection via Generalized Approximate Message Passing—0
Adaptive-Rate Compressive Sensing Using Side Information—0
Speeding-Up Convergence via Sequential Subspace Optimization: Current State and Future Directions—0
New explicit thresholding/shrinkage formulas for one class of regularization problems with overlapping group sparsity and their applications—0
Designed Measurements for Vector Count Data—0
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization—0
Dictionary-Learning-Based Reconstruction Method for Electron Tomography—0
Compressive Measurement Designs for Estimating Structured Signals in Structured Clutter: A Bayesian Experimental Design Approach—0
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive VideoCode0
A Parallel Compressive Imaging Architecture for One-Shot Acquisition—0
Parameterless Optimal Approximate Message Passing—0
Compressed Sensing SAR Imaging with Multilook Processing—0
Optimal Sensor Placement and Enhanced Sparsity for Classification—0
Energy-aware adaptive bi-Lipschitz embeddings—0
On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements—0
Multi-view in Lensless Compressive Imaging—0
Robust Canonical Time Warping for the Alignment of Grossly Corrupted Sequences—0
Lensless Imaging by Compressive Sensing—0
Compressive Sensing of Sparse Tensors—0
How to find real-world applications for compressive sensing—0
Compressive adaptive computational ghost imaging—0
Compressive Shift Retrieval—0
Group-Sparse Model Selection: Hardness and Relaxations—0
Matching Pursuit LASSO Part II: Applications and Sparse Recovery over Batch Signals—0
Adaptive Temporal Compressive Sensing for Video—0
Adaptive low rank and sparse decomposition of video using compressive sensing—0
Generalized Bregman Divergence and Gradient of Mutual Information for Vector Poisson Channels—0
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization—0
CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem—0
Compressive neural representation of sparse, high-dimensional probabilities—0
Compressive Sensing MRI with Wavelet Tree Sparsity—0
Feature-aware Label Space Dimension Reduction for Multi-label Classification—0
Forest Sparsity for Multi-channel Compressive Sensing—0
Stable and robust sampling strategies for compressive imaging—0
Robust Dequantized Compressive Sensing—0
Compressive Acquisition of Dynamic Scenes—0
Sparse Estimation with Structured Dictionaries—0
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements—0
Group Sparse Coding with a Laplacian Scale Mixture Prior—0
Fast L1-Minimization Algorithms For Robust Face RecognitionCode0
Fast L1-Minimization Algorithms For Robust Face Recognition—0
Efficient Recovery of Jointly Sparse Vectors—0
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations—0
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME)—0
Sparse Signal Recovery Using Markov Random Fields—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