Integrated Low-Rank-Based Discriminative Feature Learning for Recognition
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Chao Zhang | Pan Zhou | Zhouchen Lin | Pan Zhou | Zhouchen Lin | Chao Zhang
[1] Zhiwei Li,et al. Max-Margin Dictionary Learning for Multiclass Image Categorization , 2010, ECCV.
[2] Lei Zhang,et al. Gabor Feature Based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary , 2010, ECCV.
[3] Chao Zhang,et al. A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank , 2013, ECML/PKDD.
[4] Allen Y. Yang,et al. Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Zihan Zhou,et al. Towards a practical face recognition system: Robust registration and illumination by sparse representation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[6] W. Marsden. I and J , 2012 .
[7] Jean Ponce,et al. Learning mid-level features for recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[8] Zhouchen Lin,et al. Analysis and Improvement of Low Rank Representation for Subspace segmentation , 2010, ArXiv.
[9] Larry S. Davis,et al. Learning Structured Low-Rank Representations for Image Classification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[10] Cor J. Veenman,et al. Visual Word Ambiguity , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Yi Ma,et al. Robust principal component analysis? , 2009, JACM.
[12] Junbin Gao,et al. Relations Among Some Low-Rank Subspace Recovery Models , 2014, Neural Computation.
[13] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[14] Yuxiao Hu,et al. Learning a Spatially Smooth Subspace for Face Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Lei Wang,et al. In defense of soft-assignment coding , 2011, 2011 International Conference on Computer Vision.
[16] David Zhang,et al. Collaborative Representation based Classification for Face Recognition , 2012, ArXiv.
[17] A. Bruckstein,et al. K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .
[18] Jie Zhang,et al. Structure-Constrained Low-Rank Representation , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[19] Gene H. Golub,et al. Tikhonov Regularization and Total Least Squares , 1999, SIAM J. Matrix Anal. Appl..
[20] Yong Yu,et al. Robust Subspace Segmentation by Low-Rank Representation , 2010, ICML.
[21] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[22] G. Sapiro,et al. A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography. , 2013, Journal of structural biology.
[23] Mubarak Shah,et al. Recognizing 50 human action categories of web videos , 2012, Machine Vision and Applications.
[24] Jason J. Corso,et al. Action bank: A high-level representation of activity in video , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[25] Jian Yang,et al. Robust sparse coding for face recognition , 2011, CVPR 2011.
[26] Aleix M. Martinez,et al. The AR face database , 1998 .
[27] Zhixun Su,et al. Solving Principal Component Pursuit in Linear Time via $l_1$ Filtering , 2011, ArXiv.
[28] Cor J. Veenman,et al. Kernel Codebooks for Scene Categorization , 2008, ECCV.
[29] Jean Ponce,et al. Task-Driven Dictionary Learning , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Subhransu Maji,et al. Efficient Classification for Additive Kernel SVMs , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[32] Shuicheng Yan,et al. Latent Low-Rank Representation for subspace segmentation and feature extraction , 2011, 2011 International Conference on Computer Vision.
[33] Antonio Torralba,et al. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.
[34] Yu-Chiang Frank Wang,et al. Low-rank matrix recovery with structural incoherence for robust face recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[35] Zhixun Su,et al. Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation , 2011, NIPS.
[36] Qionghai Dai,et al. Low-Rank Structure Learning via Nonconvex Heuristic Recovery , 2010, IEEE Transactions on Neural Networks and Learning Systems.
[37] Junbin Gao,et al. Linear time Principal Component Pursuit and its extensions using ℓ1 filtering , 2014, Neurocomputing.
[38] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[39] David J. Kriegman,et al. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[40] A. Martínez,et al. The AR face databasae , 1998 .
[41] Andrew Y. Ng,et al. The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization , 2011, ICML.
[42] Larry S. Davis,et al. Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] Yihong Gong,et al. Linear spatial pyramid matching using sparse coding for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[44] Yong Yu,et al. Robust Recovery of Subspace Structures by Low-Rank Representation , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Yi Ma,et al. The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices , 2010, Journal of structural biology.
[46] David J. Kriegman,et al. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.
[47] Cordelia Schmid,et al. Evaluation of Local Spatio-temporal Features for Action Recognition , 2009, BMVC.
[48] Tieniu Tan,et al. Salient coding for image classification , 2011, CVPR 2011.
[49] Y. Jiang,et al. Spectral Clustering on Multiple Manifolds , 2011, IEEE Transactions on Neural Networks.
[50] Francis R. Bach,et al. Structured Variable Selection with Sparsity-Inducing Norms , 2009, J. Mach. Learn. Res..
[51] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[52] Massimiliano Pontil,et al. Multi-Task Feature Learning , 2006, NIPS.
[53] René Vidal,et al. A closed form solution to robust subspace estimation and clustering , 2011, CVPR 2011.
[54] Shimon Ullman,et al. Uncovering shared structures in multiclass classification , 2007, ICML '07.
[55] Terence Sim,et al. The CMU Pose, Illumination, and Expression Database , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[56] Ivan Laptev,et al. On Space-Time Interest Points , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[57] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[58] Pietro Perona,et al. A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[59] Liang-Tien Chia,et al. Local features are not lonely – Laplacian sparse coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[60] K. Schittkowski,et al. NONLINEAR PROGRAMMING , 2022 .