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Explicit encoding of group actions in deep features makes it possible for convolutional neural networks (CNNs) to handle global deformations of images, which is critical to success in many vision tasks.
The design and use of steerable filters
William T. Freeman, Edward H. Adelson, et al · 1991
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Double sparsity: Learning sparse dictionaries for sparse signal approximation
Ron Rubinstein, Michael Zibulevsky, and Michael Elad · 2010
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Transforming auto-encoders
Geoffrey E. Hinton, Alex Krizhevsky, and Sida D. Wang · 2011
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Transformation equivariant boltzmann machines
Jyri J. Kivinen and Christopher K. I. Williams · 2011
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Learning rotation-aware features: From invariant priors to equivariant descriptors
Uwe Schmidt and Stefan Roth · 2012
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Learning rotation-aware features: From invariant priors to equivariant descriptors
Uwe Schmidt and Stefan Roth · 2012
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Learning separable filters
Roberto Rigamonti, Amos Sironi, Vincent Lepetit, and Pascal Fua · 2013
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Rotation, scaling and deformation invariant scattering for texture discrimination
Laurent Sifre and Stéphane Mallat · 2013
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Exploiting linear structure within convolutional networks for efficient evaluation
Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, and Rob Fergus · 2014
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Speeding up convolutional neural networks with low rank expansions
Max Jaderberg, Andrea Vedaldi, and Andrew Zisserman · 2014
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One millisecond face alignment with an ensemble of regression trees
Vahid Kazemi and Josephine Sullivan · 2014
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Speeding-up convolutional neural networks using fine-tuned cp-decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan Oseledets, and Victor Lempitsky · 2014
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A data-driven approach to cleaning large face datasets
Hong-Wei Ng and Stefan Winkler · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Wenlin Chen, James Wilson, Stephen Tyree, Kilian Weinberger, and Yixin Chen · 2015
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Sam Hallman and Charless C. Fowlkes · 2015
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Learning both weights and connections for efficient neural network
Song Han, Jeff Pool, John Tran, and William J. Dally · 2015
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
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Max Jaderberg, Karen Simonyan, Andrew Zisserman, and Koray Kavukcuoglu · 2015
Learning rotation invariant convolutional filters for texture classification
Diego M. Gonzalez, Michele Volpi, and Devis Tuia · 2016
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J. Dally · 2016
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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5mb model size
Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, and Kurt Keutzer · 2016
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Ti-pooling: transformation-invariant pooling for feature learning in convolutional neural networks
Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, and Marc Pollefeys · 2016
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Convolutional oriented boundaries
Kevis-K. Maninis, Jordi Pont-Tuset, Pablo Arbeláez, and Luc Van Gool · 2016
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Deep roto-translation scattering for object classification
Edouard Oyallon and Stéphane Mallat · 2015
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Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
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Convolutional neural networks with low-rank regularization
Cheng Tai, Tong Xiao, Yi Zhang, Xiaogang Wang, et al · 2015
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Fa Wu, Peijun Hu, and Dexing Kong · 2015
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Group equivariant convolutional networks
Taco S. Cohen and Max Welling · 2016
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Learning deep features for discriminative localization
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Convolutional neural networks analyzed via convolutional sparse coding
Vardan Papyan, Yaniv Romano, and Michael Elad · 2017
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Learning steerable filters for rotation equivariant cnns
Maurice Weiler, Fred A. Hamprecht, and Martin Storath · 2017
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Harmonic networks: Deep translation and rotation equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, and Gabriel J. Brostow · 2017
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Oriented response networks
Yanzhao Zhou, Qixiang Ye, Qiang Qiu, and Jianbin Jiao · 2017
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Taco S. Cohen, Mario Geiger, Jonas Koehler, and Max Welling · 2018
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DCFNet: Deep neural network with decomposed convolutional filters
Qiang Qiu, Xiuyuan Cheng, Robert Calderbank, and Guillermo Sapiro · 2018
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