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Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potential for improving representation and generalization abilities of deep CNNs.
C. Stein, “Lectures on the theory of estimation of many parameters,” Journal of Soviet Mathematics , vol. 34, no. 1, pp. 1373–1403, 1986
1986
Earlier work this paper cites.
M. Calvo and J. M. Oller, “A distance between multivariate normal distributions based on an embedding into the Siegel group,” JMVA , vol. 35, no. 2, pp. 223–242, 1990
1990
Earlier work this paper cites.
M. Lovric, M. Min-Oo, and E. A. Ruh, “Multivariate normal distributions parametrized as a Riemannian symmetric space,” JMVA , vol. 74, no. 1, pp. 36–48, 2000
2000
Earlier work this paper cites.
M. J. Daniels and R. E. Kass, “Shrinkage estimators for covariance matrices,” Biometrics , vol. 57, no. 4, pp. 1173–1184, 2001
2001
Earlier work this paper cites.
D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” IJCV , vol. 60, no. 2, pp. 91–110, 2004
2004
Earlier work this paper cites.
O. Ledoit and M. Wolf, “A well-conditioned estimator for large-dimensional covariance matrices,” J. Multivariate Analysis , vol. 88, no. 2, pp. 365–411, 2004
2004
Earlier work this paper cites.
V. Arsigny, P. Fillard, X. Pennec, and N. Ayache, “Fast and simple calculus on tensors in the Log-Euclidean framework,” in MICCAI , 2005
2005
Earlier work this paper cites.
O. Tuzel, F. Porikli, and P. Meer, “Region covariance: A fast descriptor for detection and classification,” in ECCV , 2006
2006
Earlier work this paper cites.
X. Pennec, P. Fillard, and N. Ayache, “A Riemannian framework for tensor computing,” IJCV , vol. 66, no. 1, pp. 41–66, 2006
2006
Earlier work this paper cites.
N. J. Higham, Functions of Matrices: Theory and Computation . Philadelphia, PA, USA: Society for Industrial and Applied Mathematics, 2008
2008
Earlier work this paper cites.
L. Dryden, A. Koloydenko, and D. Zhou, “Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging,” The Annals of Applied Statistics , 2009
2009
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in CVPR , 2009
2009
Earlier work this paper cites.
A. Quattoni and A. Torralba, “Recognizing indoor scenes,” in CVPR , 2009
2009
Earlier work this paper cites.
T. G. Kolda and B. W. Bader, “Tensor decompositions and applications,” SIAM Review , vol. 51, no. 3, pp. 455–500, 2009
2009
Earlier work this paper cites.
L. Gong, T. Wang, and F. Liu, “Shape of Gaussians as feature descriptors,” in CVPR , 2009
2009
Earlier work this paper cites.
Y. Chen, A. Wiesel, Y. C. Eldar, and A. O. Hero, “Shrinkage algorithms for MMSE covariance estimation.” IEEE TSP , vol. 58, no. 10, pp. 5016–5029, 2010
2010
Earlier work this paper cites.
H. Nakayama, T. Harada, and Y. Kuniyoshi, “Global Gaussian approach for scene categorization using information geometry,” in CVPR , 2010
2010
Earlier work this paper cites.
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie, “The Caltech-UCSD Birds-200-2011 Dataset,” California Institute of Technology, Tech. Rep. CNS-TR-2011-001, 2011
2011
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” in NIPS , 2012
2012
Earlier work this paper cites.
H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez, and C. Schmid, “Aggregating local image descriptors into compact codes,” IEEE TPAMI , vol. 34, no. 9, pp. 1704–1716, 2012
2012
Earlier work this paper cites.
Y. Bengio, A. Courville, and P. Vincent, “Representation learning: A review and new perspectives,” IEEE TPAMI , vol. 35, no. 8, pp. 1798–1828, 2013
2013
Earlier work this paper cites.
J. Sanchez, F. Perronnin, T. Mensink, and J. Verbeek, “Image classification with the Fisher vector: Theory and practice,” IJCV , vol. 105, no. 3, pp. 222–245, 2013
2013
Earlier work this paper cites.
S. Maji, J. Kannala, E. Rahtu, M. Blaschko, and A. Vedaldi, “Fine-grained visual classification of aircraft,” Tech. Rep., 2013
2013
Earlier work this paper cites.
J. Krause, M. Stark, J. Deng, and L. Fei-Fei, “3D object representations for fine-grained categorization,” in Workshop on 3D Representation and Recognition, ICCV , 2013
2013
Earlier work this paper cites.
P. Li, Q. Wang, and L. Zhang, “A novel earth mover’s distance methodology for image matching with gaussian mixture models,” in ICCV , 2013, pp. 1689–1696
2013
Earlier work this paper cites.
D. L. Donoho, M. Gavish, and I. M. Johnstone, “Optimal shrinkage of eigenvalues in the spiked covariance model,” arXiv , vol. 1311.0851, 2014
2014
Cited alongside, same era.
M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, and A. Vedaldi, “Describing textures in the wild,” in CVPR , 2014
2014
Cited alongside, same era.
E. Yang, A. Lozano, and P. Ravikumar, “Elementary estimators for sparse covariance matrices and other structured moments,” in ICML , 2014
2014
Cited alongside, same era.
M. Lin, Q. Chen, and S. Yan, “Network in network,” in ICLR , 2014
2014
Cited alongside, same era.
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman, “Return of the devil in the details: Delving deep into convolutional nets,” in BMVC , 2014
2014
Cited alongside, same era.
P. Koniusz, F. Yan, P. Gosselin, and K. Mikolajczyk, “Higher-order occurrence pooling for bags-of-words: Visual concept detection,” IEEE TPAMI , vol. 39, no. 2, pp. 313–326, 2017
2017
Later among the works it cites.
P. Li, Q. Wang, H. Zeng, and L. Zhang, “Local Log-Euclidean multivariate Gaussian descriptor and its application to image classification,” IEEE TPAMI , vol. 39, no. 4, pp. 803–817, 2017
2017
Later among the works it cites.
T.-Y. Lin and S. Maji, “Improved bilinear pooling with CNNs,” in BMVC , 2017
2017
Later among the works it cites.
S. Xie, R. B. Girshick, P. Dollár, Z. Tu, and K. He, “Aggregated residual transformations for deep neural networks,” in CVPR , 2017
2017
Later among the works it cites.
P. Li, J. Xie, Q. Wang, and W. Zuo, “Is second-order information helpful for large-scale visual recognition?” in ICCV , 2017
2017
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M. D. Zeiler and R. Fergus, “Visualizing and understanding convolutional networks,” in ECCV , 2014
2014
Cited alongside, same era.
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, “Overfeat: Integrated recognition, localization and detection using convolutional networks,” in ICLR , 2014
2014
Cited alongside, same era.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” in ICLR , 2015
2015
Cited alongside, same era.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in CVPR , 2015
2015
Cited alongside, same era.
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu, “Free-form region description with second-order pooling,” IEEE TPAMI , vol. 37, no. 6, pp. 1177–1189, 2015
2015
Cited alongside, same era.
C. Ionescu, O. Vantzos, and C. Sminchisescu, “Matrix backpropagation for deep networks with structured layers,” in ICCV , 2015
2015
Cited alongside, same era.
T.-Y. Lin, A. RoyChowdhury, and S. Maji, “Bilinear CNN models for fine-grained visual recognition,” in ICCV , 2015
2015
Cited alongside, same era.
Later among the works it cites.
Q. Wang, P. Li, and L. Zhang, “G 2 DeNet: Global Gaussian distribution embedding network and its application to visual recognition,” in CVPR , 2017
2017
Later among the works it cites.
S. Kong and C. Fowlkes, “Low-rank bilinear pooling for fine-grained classification,” in CVPR , 2017
2017
Later among the works it cites.
X. Dai, J. Yue-Hei Ng, and L. S. Davis, “FASON: First and second order information fusion network for texture recognition,” in CVPR , 2017
2017
Later among the works it cites.
Y. Cui, F. Zhou, J. Wang, X. Liu, Y. Lin, and S. Belongie, “Kernel pooling for convolutional neural networks,” in CVPR , 2017
2017
Later among the works it cites.
S. Cai, W. Zuo, and L. Zhang, “Higher-order integration of hierarchical convolutional activations for fine-grained visual categorization,” in ICCV , 2017
2017
Later among the works it cites.
Y. Li, N. Wang, J. Liu, and X. Hou, “Factorized bilinear models for image recognition,” in ICCV , 2017
2017
Later among the works it cites.
Y. Wang, L. Xie, C. Liu, S. Qiao, Y. Zhang, W. Zhang, Q. Tian, and A. Yuille, “SORT: Second-order response transform for visual recognition,” in ICCV , 2017
2017
Later among the works it cites.
Y. Li, M. Dixit, and N. Vasconcelos, “Deep scene image classification with the MFAFVNet,” in ICCV , 2017
2017
Later among the works it cites.
H. Zhang, J. Xue, and K. J. Dana, “Deep TEN: Texture encoding network,” in CVPR , 2017
2017
Later among the works it cites.
S. Ren, K. He, R. B. Girshick, and J. Sun, “Faster R-CNN: towards real-time object detection with region proposal networks,” IEEE TPAMI , vol. 39, no. 6, pp. 1137–1149, 2017
2017
Later among the works it cites.
E. Shelhamer, J. Long, and T. Darrell, “Fully convolutional networks for semantic segmentation,” IEEE TPAMI , vol. 39, no. 4, pp. 640–651, 2017
2017
Later among the works it cites.
P. Li, J. Xie, Q. Wang, and Z. Gao, “Towards faster training of global covariance pooling networks by iterative matrix square root normalization,” in CVPR , 2018
2018
Later among the works it cites.
B. Zhou, À. Lapedriza, A. Khosla, A. Oliva, and A. Torralba, “Places: A 10 million image database for scene recognition,” IEEE TPAMI , vol. 40, no. 6, pp. 1452–1464, 2018
2018
Later among the works it cites.
D. Acharya, Z. Huang, D. Pani Paudel, and L. Van Gool, “Covariance pooling for facial expression recognition,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops on Diff-CVML , 2018
2018
Later among the works it cites.
K. Yu and M. Salzmann, “Statistically-motivated second-order pooling,” in ECCV , 2018, pp. 621–637
2018
Later among the works it cites.
J. Hu, L. Shen, and G. Sun, “Squeeze-and-excitation networks,” in CVPR , 2018
2018
Later among the works it cites.
C. Woo, J. Park, J.-Y. Lee, and I. S. Kweon, “CBAM: Convolutional block attention module,” in ECCV , 2018
2018
Later among the works it cites.
T. Lin, A. Roy Chowdhury, and S. Maji, “Bilinear convolutional neural networks for fine-grained visual recognition,” IEEE TPAMI , vol. 40, no. 6, pp. 1309–1322, 2018
2018
Later among the works it cites.
Z. Huang, R. Wang, X. Li, W. Liu, S. Shan, L. V. Gool, and X. Chen, “Geometry-aware similarity learning on SPD manifolds for visual recognition,” IEEE Trans. Circuits Syst. Video Techn. , vol. 28, no. 10, pp. 2513–2523, 2018
2018
Later among the works it cites.