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We introduce a novel self-supervised learning method based on adversarial training.
Autoencoders, minimum description length, and helmholtz free energy
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Image inpainting
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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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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
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An analysis of single-layer networks in unsupervised feature learning
A. Coates, A. Ng, and H. Lee · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
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Multi-task bayesian optimization
K. Swersky, J. Snoek, and R. P. Adams · 2013
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Discriminative unsupervised feature learning with convolutional neural networks
A. Dosovitskiy, J. T. Springenberg, M. Riedmiller, and T. Brox · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Cnn features off-the-shelf: an astounding baseline for recognition
A. Sharif Razavian, H. Azizpour, J. Sullivan, and S. Carlsson · 2014
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Learning deep features for scene recognition using places database
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva · 2014
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Learning to see by moving
P. Agrawal, J. Carreira, and J. Malik · 2015
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Unsupervised visual representation learning by context prediction
C. Doersch, A. Gupta, and A. A. Efros · 2015
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Convolutional clustering for unsupervised learning
A. Dundar, J. Jin, and E. Culurciello · 2015
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Fast r-cnn
R. Girshick · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Learning image representations tied to ego-motion
D. Jayaraman and K. Grauman · 2015
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Data-dependent initializations of convolutional neural networks
Unsupervised learning of discriminative attributes and visual representations
C. Huang, C. Change Loy, and X. Tang · 2016
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Shuffle and learn: unsupervised learning using temporal order verification
I. Misra, C. L. Zitnick, and M. Hebert · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
M. Noroozi and P. Favaro · 2016
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Ambient sound provides supervision for visual learning
A. Owens, J. Wu, J. H. McDermott, W. T. Freeman, and A. Torralba · 2016
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Context encoders: Feature learning by inpainting
D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros · 2016
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The curious robot: Learning visual representations via physical interactions
L. Pinto, D. Gandhi, Y. Han, Y.-L. Park, and A. Gupta · 2016
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P. Krähenbühl, C. Doersch, J. Donahue, and T. Darrell · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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A. Makhzani, J. Shlens, N. Jaitly, and I. Goodfellow · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Unsupervised learning of visual representations using videos
X. Wang and A. Gupta · 2015
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Understanding neural networks through deep visualization
J. Yosinski, J. Clune, A. Nguyen, T. Fuchs, and H. Lipson · 2015
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Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
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R. R. Selvaraju, A. Das, R. Vedantam, M. Cogswell, D. Parikh, and D. Batra · 2016
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Learning from simulated and unsupervised images through adversarial training
A. Shrivastava, T. Pfister, O. Tuzel, J. Susskind, W. Wang, and R. Webb · 2016
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Colorful image colorization
R. Zhang, P. Isola, and A. A. Efros · 2016
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Unsupervised learning by predicting noise
P. Bojanowski and A. Joulin · 2017
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Colorization as a proxy task for visual understanding
G. Larsson, M. Maire, and G. Shakhnarovich · 2017
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Representation learning by learning to count
M. Noroozi, H. Pirsiavash, and P. Favaro · 2017
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Learning features by watching objects move
D. Pathak, R. Girshick, P. Dollár, T. Darrell, and B. Hariharan · 2017
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Split-brain autoencoders: Unsupervised learning by cross-channel prediction
R. Zhang, P. Isola, and A. A. Efros · 2017
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