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 176–200 of 597 papers

TitleStatusHype
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
Monotonically Convergent Regularization by Denoising—0
Image-to-Image MLP-mixer for Image ReconstructionCode0
Unsupervised Sparse Unmixing of Atmospheric Trace Gases from Hyperspectral Satellite Data—0
Low dosage 3D volume fluorescence microscopy imaging using compressive sensing—0
Generative adversarial network for super-resolution imaging through a fiber—0
HLRTF: Hierarchical Low-Rank Tensor Factorization for Inverse Problems in Multi-Dimensional Imaging—0
An Off-grid Compressive Sensing Strategy for the Subarray Synthesis of Non-uniform Linear Arrays—0
Compressive Scanning Transmission Electron Microscopy—0
More is Less: Inducing Sparsity via Overparameterization—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Differentiable Gaussianization Layers for Inverse Problems Regularized by Deep Generative ModelsCode0
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser—0
Moment Transform-Based Compressive Sensing in Image Processing—0
Optimizing Binary Symptom Checkers via Approximate Message Passing—0
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction—0
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover—0
PLUGIn-CS: A simple algorithm for compressive sensing with generative prior—0
Learning a Compressive Sensing Matrix with Structural Constraints via Maximum Mean Discrepancy Optimization—0
Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework—0
Compressive Sensing Based Adaptive Defence Against Adversarial Images—0
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation—0
Lottery Image Prior—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