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How can unlabeled video augment visual learning? Existing methods perform "slow" feature analysis, encouraging the representations of temporally close frames to exhibit only small differences.
Slow feature analysis: unsupervised learning of invariances
L. Wiskott and T. J. Sejnowski · 2002
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Simple-cell-like receptive fields maximize temporal coherence in natural video
J. Hurri and A. Hyvarinen · 2003
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Best practices for convolutional neural networks applied to visual document analysis
P. Simard, D. Steinkraus, and J.C. Platt · 2003
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Learning methods for generic object recognition with invariance to pose and lighting
Y. LeCun, F. J. Huang, and L. Bottou · 2004
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Slow feature analysis yields a rich repertoire of complex cell properties
P. Berkes and L. Wiskott · 2005
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Dimensionality Reduction by Learning an Invariant Mapping
R. Hadsell, S. Chopra, and Y. LeCun · 2006
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Unsupervised natural experience rapidly alters invariant object representation in visual cortex
N. Li and J. DiCarlo · 2008
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Extracting and composing robust features with denoising autoencoders
P. Vincent, H. Larochelle, Y. Bengio, and P.A. Manzagol · 2008
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Slow, decorrelated features for pretraining complex cell-like networks
J. Bergstra and Y. Bengio · 2009
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.J. Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images, 2009
A. Krizhevsky · 2009
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Deep Learning from Temporal Coherence in Video
H. Mobahi, R. Collobert, and J. Weston · 2009
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. Williams, J. Winn, and A. Zisserman · 2010
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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SUN database: Large-scale scene recognition from abbey to zoo
J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba · 2010
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Transforming Auto-Encoders
G. Hinton, A. Krizhevsky, and S.D. Wang · 2011
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HMDB: a large video database for human motion recognition
H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, and T. Serre · 2011
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Temporal relations in videos for unsupervised activity analysis
F. Nater, H. Grabner, and L. Van Gool · 2011
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Unsupervised learning of visual invariance with temporal coherence
Will Y Zou, Andrew Y Ng, and Kai Yu · 2011
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Are we ready for autonomous driving? the KITTI vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. Hinton · 2012
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Incremental slow feature analysis with indefinite kernel for online temporal video segmentation
S. Liwicki, S. Zafeiriou, and M. Pantic · 2012
Recognizing image style
S. Karayev, M. Trentacoste, H. Han, A. Agarwala, T. Darrell, A. Hertzmann, and H. Winnemoeller · 2014
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Modeling Deep Temporal Dependencies with Recurrent Grammar Cells
V. Michalski, R. Memisevic, and K. Konda · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J.Sivic · 2014
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Video (language) modeling: a baseline for generative models of natural videos
M. Ranzato, A. Szlam, J. Bruna, M. Mathieu, R. Collobert, and S. Chopra · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Learning to see by moving
P. Agrawal, J. Carreira, and J. Malik · 2015
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Learning rotation-aware features: From invariant priors to equivariant descriptors
U. Schmidt and S. Roth · 2012
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Slow feature analysis for human action recognition
Z. Zhang and D. Tao · 2012
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Deep learning of invariant features via simulated fixations in video
W. Zou, S. Zhu, K. Yu, and A. Ng · 2012
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Decaf: A deep convolutional activation feature for generic visual recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2013
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Learning to relate images
R. Memisevic · 2013
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Learning slow features for behaviour analysis
L. Zafeiriou, M. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic · 2013
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Learning to linearize under uncertainty
Ross Goroshin, Michael F Mathieu, and Yann LeCun · 2015
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Learning image representations tied to ego-motion
D. Jayaraman and K. Grauman · 2015
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Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video
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Understanding image representations by measuring their equivariance and equivalence
Karel Lenc and Andrea Vedaldi · 2015
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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. Berg, and L. Fei-Fei · 2015
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Anticipating the future by watching unlabeled video
C. Vondrick, H. Pirsiavash, and A. Torralba · 2015
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Dense optical flow prediction from a static image
J. Walker, A. Gupta, and M. Hebert · 2015
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Unsupervised learning of visual representations using videos
X. Wang and A. Gupta · 2015
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Importance weighted autoencoders
Y. Burda, R. Grosse, and R. Salakhutdinov · 2016
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