Compressive Sensing

75 papers with code • 5 benchmarks • 4 datasets

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

Greatest papers with code

Provable Dynamic Robust PCA or Robust Subspace Tracking

andrewssobral/lrslibrary 24 May 2017

Dynamic robust PCA refers to the dynamic (time-varying) extension of robust PCA (RPCA).

Compressive Sensing

One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models

rick-chang/OneNet 29 Mar 2017

On the other hand, traditional methods using signal priors can be used in all linear inverse problems but often have worse performance on challenging tasks.

Compressive Sensing Image Inpainting +1

ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing

jianzhangcs/ISTA-Net-PyTorch CVPR 2018

With the aim of developing a fast yet accurate algorithm for compressive sensing (CS) reconstruction of natural images, we combine in this paper the merits of two existing categories of CS methods: the structure insights of traditional optimization-based methods and the speed of recent network-based ones.

Compressive Sensing

DeepBinaryMask: Learning a Binary Mask for Video Compressive Sensing

miliadis/DeepVideoCS 12 Jul 2016

In this paper, we propose a novel encoder-decoder neural network model referred to as DeepBinaryMask for video compressive sensing.

Compressive Sensing Video Compressive Sensing +1

Deep Fully-Connected Networks for Video Compressive Sensing

miliadis/DeepVideoCS 16 Mar 2016

In this work we present a deep learning framework for video compressive sensing.

Compressive Sensing Video Compressive Sensing

Sparse Depth Sensing for Resource-Constrained Robots

sparse-depth-sensing/sparse-depth-sensing 4 Mar 2017

We address the following question: is it possible to reconstruct the geometry of an unknown environment using sparse and incomplete depth measurements?

Compressive Sensing Depth Estimation

Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

xchen-tamu/linear-lista-cpss NeurIPS 2018

In this work, we study unfolded ISTA (Iterative Shrinkage Thresholding Algorithm) for sparse signal recovery.

Compressive Sensing

One Network to Solve Them All -- Solving Linear Inverse Problems Using Deep Projection Models

image-science-lab/OneNet ICCV 2017

While deep learning methods have achieved state-of-the-art performance in many challenging inverse problems like image inpainting and super-resolution, they invariably involve problem-specific training of the networks.

Compressive Sensing Image Inpainting +1

SNIPS: Solving Noisy Inverse Problems Stochastically

bahjat-kawar/snips_torch NeurIPS 2021

In this work we introduce a novel stochastic algorithm dubbed SNIPS, which draws samples from the posterior distribution of any linear inverse problem, where the observation is assumed to be contaminated by additive white Gaussian noise.

Compressive Sensing Deblurring +2

A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

FWen/ncreg 16 Aug 2018

In recent, nonconvex regularization based sparse and low-rank recovery is of considerable interest and it in fact is a main driver of the recent progress in nonconvex and nonsmooth optimization.

Compressive Sensing Matrix Completion +1