Video Compressed Sensing Using a Convolutional Neural Network

[1]  Lu Gan Block Compressed Sensing of Natural Images , 2007, 2007 15th International Conference on Digital Signal Processing.

[2]  Namrata Vaswani,et al.  LS-CS-Residual (LS-CS): Compressive Sensing on Least Squares Residual , 2009, IEEE Transactions on Signal Processing.

[3]  Margaret H. Pinson,et al.  Temporal Video Quality Model Accounting for Variable Frame Delay Distortions , 2014, IEEE Transactions on Broadcasting.

[4]  James E. Fowler,et al.  Residual Reconstruction for Block-Based Compressed Sensing of Video , 2011, 2011 Data Compression Conference.

[5]  Chen Chen,et al.  Compressed-sensing recovery of images and video using multihypothesis predictions , 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

[6]  Charless C. Fowlkes,et al.  Contour Detection and Hierarchical Image Segmentation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Fengbo Ren,et al.  LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction , 2018, ECCV.

[8]  Wen Gao,et al.  Video Compressive Sensing Reconstruction via Reweighted Residual Sparsity , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[9]  Ramesh Raskar,et al.  Coded Strobing Photography: Compressive Sensing of High Speed Periodic Videos , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Rajiv Soundararajan,et al.  Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[11]  James E. Fowler,et al.  Block-Based Compressed Sensing of Images and Video , 2012, Found. Trends Signal Process..

[12]  S. Frick,et al.  Compressed Sensing , 2014, Computer Vision, A Reference Guide.

[13]  James E. Fowler,et al.  Block Compressed Sensing of Images Using Directional Transforms , 2010, 2010 Data Compression Conference.

[14]  Shree K. Nayar,et al.  Video from a single coded exposure photograph using a learned over-complete dictionary , 2011, 2011 International Conference on Computer Vision.

[15]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[16]  Wei Lu,et al.  Modified-CS: Modifying compressive sensing for problems with partially known support , 2009, 2009 IEEE International Symposium on Information Theory.

[17]  Feng Jiang,et al.  Scalable Convolutional Neural Network for Image Compressed Sensing , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  Wen Gao,et al.  Group-Based Sparse Representation for Image Restoration , 2014, IEEE Transactions on Image Processing.

[19]  Ting Sun,et al.  Single-pixel imaging via compressive sampling , 2008, IEEE Signal Process. Mag..

[20]  Alan C. Bovik,et al.  Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos , 2010, IEEE Transactions on Image Processing.

[21]  Emmanuel J. Candès,et al.  Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.

[22]  Margaret H. Pinson,et al.  A new standardized method for objectively measuring video quality , 2004, IEEE Transactions on Broadcasting.

[23]  James E. Fowler,et al.  Video Compressed Sensing with Multihypothesis , 2011, 2011 Data Compression Conference.

[24]  Andrea Vedaldi,et al.  MatConvNet: Convolutional Neural Networks for MATLAB , 2014, ACM Multimedia.

[25]  Jian Sun,et al.  Deep ADMM-Net for Compressive Sensing MRI , 2016, NIPS.

[26]  Richard G. Baraniuk,et al.  Compressive imaging for video representation and coding , 2006 .

[27]  Richard G. Baraniuk,et al.  A deep learning approach to structured signal recovery , 2015, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[28]  Geoffrey E. Hinton,et al.  Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.

[29]  Mathews Jacob,et al.  Accelerated Dynamic MRI Exploiting Sparsity and Low-Rank Structure: k-t SLR , 2011, IEEE Transactions on Medical Imaging.

[30]  Wuzhen Shi,et al.  Deep networks for compressed image sensing , 2017, 2017 IEEE International Conference on Multimedia and Expo (ICME).

[31]  Feng Jiang,et al.  Image Compressed Sensing Using Convolutional Neural Network , 2020, IEEE Transactions on Image Processing.

[32]  Hancheng Lu,et al.  FompNet: Compressive sensing reconstruction with deep learning over wireless fading channels , 2017, 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP).

[33]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[34]  Pavan K. Turaga,et al.  ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[35]  Rama Chellappa,et al.  P2C2: Programmable pixel compressive camera for high speed imaging , 2011, CVPR 2011.

[36]  Bernard Ghanem,et al.  ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.