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 126–150 of 597 papers

TitleStatusHype
A Fast Alternating Minimization Algorithm for Coded Aperture Snapshot Spectral Imaging Based on Sparsity and Deep Image Priors—0
Compressive Sensing with Wigner D-functions on Subsets of the Sphere—0
Memory-efficient model-based deep learning with convergence and robustness guarantees—0
Machine Learning Prediction for Phase-less Millimeter-Wave Beam Tracking—0
Single pixel imaging at high pixel resolutions—0
Compressive Fourier collocation methods for high-dimensional diffusion equations with periodic boundary conditions—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive ImagingCode0
Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation—0
Nonconvex L_ 1/2 -Regularized Nonlocal Self-similarity Denoiser for Compressive Sensing based CT Reconstruction—0
DECONET: an Unfolding Network for Analysis-based Compressed Sensing with Generalization Error Bounds—0
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural NetworksCode1
Signal Recovery with Non-Expansive Generative Network Priors—0
Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed SensingCode1
FSOINet: Feature-Space Optimization-Inspired Network for Image Compressive SensingCode1
Blind Orthogonal Least Squares based Compressive Spectrum Sensing—0
A General Compressive Sensing Construct using Density Evolution—0
Adaptive and Cascaded Compressive Sensing—0
Learning Nonlocal Sparse and Low-Rank Models for Image Compressive SensingCode1
The Role of Interactivity in Structured Estimation—0
One-Bit Compressive Sensing: Can We Go Deep and Blind?—0
Coarse-to-Fine Sparse Transformer for Hyperspectral Image ReconstructionCode0
_1DecNet+: A new architecture framework by _1 decomposition and iteration unfolding for sparse feature segmentation—0
HDNet: High-resolution Dual-domain Learning for Spectral Compressive ImagingCode0
Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing—0
Mathematical Foundation of Sparsity-based Multi-snapshot Spectral Estimation—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