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Learning visual representations with self-supervised learning has become popular in computer vision.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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Sparse coding with an overcomplete basis set: A strategy employed by v1?
B. A. Olshausen and D. J. Field · 1997
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Distinctive Image Features from Scale-Invariant Keypoints
D. Lowe · 2004
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Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, and Y. LeCun · 2005
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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Discovering objects and their location in images
J. Sivic, B. C. Russell, A. A. Efros, A. Zisserman, and W. T. Freeman · 2005
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Surf: Speeded up robust features
H. Bay, T. Tuytelaars, and L. V. Gool · 2006
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Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun · 2006
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Reducing the dimensionality of data with neural networks
G. E. Hinton and R. R. Salakhutdinov · 2006
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Using multiple segmentations to discover objects and their extent in image collections
B. C. Russell, A. A. Efros, J. Sivic, W. T. Freeman, and A. Zisserman · 2006
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Greedy layer-wise training of deep networks
Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle · 2007
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Extracting and composing robust features with denoising autoencoders
P. Vincent, H. Larochelle, Y. Bengio, and P. Manzagol · 2008
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng · 2009
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The Pascal Visual Object Classes (VOC) Challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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The shape boltzmann machine: a strong model of object shape
S. M. A. Eslami, N. Heess, and J. Winn · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Building high-level features using large scale unsupervised learning
Q. V. Le, M. A. Ranzato, R. Monga, M. Devin, K. Chen, G. S. Corrado, J. Dean, and A. Y. Ng · 2012
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Indoor segmentation and support inference from RGBD images
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
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Unsupervised discovery of mid-level discriminative patches
S. Singh, A. Gupta, and A. A. Efros · 2012
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Robust boltzmann machines for recognition and denoising
Y. Tang, R. Salakhutdinov, and G. Hinton · 2012
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Mid-level visual element discovery as discriminative mode seeking
C. Doersch, A. Gupta, and A. A. Efros · 2013
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Data-driven 3D primitives for single image understanding
D. F. Fouhey, A. Gupta, and M. Hebert · 2013
Cited alongside, same era.
Deep convolutional ranking for multilabel image annotation
Y. Gong, Y. Jia, T. K. Leung, A. Toshev, and S. Ioffe · 2013
Cited alongside, same era.
Selective search for object recognition
J. Uijlings, K. van de Sande, T. Gevers, and A. Smeulders · 2013
Cited alongside, same era.
Action recognition with improved trajectories
H. Wang and C. Schmid · 2013
Cited alongside, same era.
Context as supervisory signal: Discovering objects with predictable context
C. Doersch, A. Gupta, and A. A. Efros · 2014
Cited alongside, same era.
Unfolding an indoor origami world
D. F. Fouhey, A. Gupta, and M. Hebert · 2014
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Deep multi-scale video prediction beyond mean square error
M. Mathieu, C. Couprie, and Y. LeCun · 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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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. C. Berg, and L. Fei-Fei · 2015
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Unsupervised learning of video representations using LSTMs
N. Srivastava, E. Mansimov, and R. Salakhutdinov · 2015
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Designing deep networks for surface normal estimation
X. Wang, D. F. Fouhey, and A. Gupta · 2015
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Cited alongside, same era.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Cited alongside, same era.
Auto-encoding variational bayes
D. Kingma and M. Welling · 2014
Cited alongside, same era.
Discriminatively trained dense surface normal estimation
L. Ladický, B. Zeisl, and M. Pollefeys · 2014
Cited alongside, same era.
Computational baby learning
X. Liang, S. Liu, Y. Wei, L. Liu, L. Lin, and S. Yan · 2014
Cited alongside, same era.
Microsoft COCO: common objects in context
T. Lin, M. Maire, S. Belongie, L. D. Bourdev, R. B. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Cited alongside, same era.
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Unsupervised learning of visual representations using videos
X. Wang and A. Gupta · 2015
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Object detectors emerge in deep scene cnns
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2015
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Adversarial feature learning
J. Donahue, P. Krähenbühl, and T. Darrell · 2016
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Adversarially learned inference
V. Dumoulin, I. Belghazi, B. Poole, A. Lamb, M. Arjovsky, O. Mastropietro, and A. Courville · 2016
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Learning representations for automatic colorization
G. Larsson, M. Maire, and G. Shakhnarovich · 2016
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Unsupervised learning of edges
Y. Li, M. Paluri, J. M. Rehg, and P. Dollár · 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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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
L. Pinto and A. Gupta · 2016
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An uncertain future: Forecasting from variational autoencoders
J. Walker, C. Doersch, A. Gupta, and M. Hebert · 2016
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3D Representations via Pose Estimation and Matching
A. R. Zamir, T. Wekel, P. Agrawal, C. Wei, J. Malik, and S. Savarese · 2016
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Colorful image colorization
R. Zhang, P. Isola, and A. A. Efros · 2016
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Colorization as a proxy task for visual understanding
G. Larsson, M. Maire, and G. Shakhnarovich · 2017
Closest in time.
Unsupervised Learning of Long-Term Motion Dynamics for Videos
Z. Luo, B. Peng, D.-A. Huang, A. Alahi, and L. Fei-Fei · 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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Unsupervised Learning of Depth and Ego-motion from Video
T. Zhou, M. Brown, N. Snavely, and D. Lowe · 2017
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