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"If I provide you a face image of mine (without telling you the actual age when I took the picture) and a large amount of face images that I crawled (containing labeled faces of different ages but not necessarily paired), can you show me what I would look like when I am 80 or what I was like when I was 5?" The answer is probably a "No." Most existing face aging works attempt to learn the transformation between age groups and thus would require the paired samples as well as the labeled query image.
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D. M. Burt and D. I. Perrett · 1995
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B. Tiddeman, M. Burt, and D. Perrett · 2001
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Toward automatic simulation of aging effects on face images
A. Lanitis, C. J. Taylor, and T. F. Cootes · 2002
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Z. Liu, Z. Zhang, and Y. Shan · 2004
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Y. Fu and N. Zheng · 2006
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N. Ramanathan and R. Chellappa · 2006
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N. Ramanathan and R. Chellappa · 2008
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A compositional and dynamic model for face aging
J. Suo, S.-C. Zhu, S. Shan, and X. Chen · 2010
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A concatenational graph evolution aging model
J. Suo, X. Chen, S. Shan, W. Gao, and Q. Dai · 2012
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Y. Tazoe, H. Gohara, A. Maejima, and S. Morishima · 2012
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
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Cross-age reference coding for age-invariant face recognition and retrieval
B.-C. Chen, C.-S. Chen, and W. H. Hsu · 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
Cited alongside, same era.
Illumination-aware age progression
I. Kemelmacher-Shlizerman, S. Suwajanakorn, and S. M. Seitz · 2014
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ADAM: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Personalized age progression with aging dictionary
X. Shu, J. Tang, H. Lai, L. Liu, and S. Yan · 2015
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InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets
X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel · 2016
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Generating images with recurrent adversarial networks
D. J. Im, C. D. Kim, H. Jiang, and R. Memisevic · 2016
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Coupled generative adversarial networks
M. Y. Liu and O. Tuzel · 2016
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Adversarial autoencoders
A. Makhzani, J. Shlens, N. Jaitly, and I. Goodfellow · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
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M. Mirza and S. Osindero · 2014
Cited alongside, same era.
Deep generative image models using a laplacian pyramid of adversarial networks
E. L. Denton, S. Chintala, R. Fergus, et al · 2015
Cited alongside, same era.
Draw: A recurrent neural network for image generation
K. Gregor, I. Danihelka, A. Graves, D. J. Rezende, and D. Wierstra · 2015
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Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sønderby, and O. Winther · 2015
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Age and gender classification using convolutional neural networks
G. Levi and T. Hassner · 2015
Cited alongside, same era.
http://dlib.net/
Dlib C++ Library
Cited in the paper.
http://cherry.dcs.aber.ac.uk/transformer/
Face Transformer (FT) demo
Cited in the paper.
A. Radford, L. Metz, and S. Chintala · 2016
Later among the works it cites.
Recurrent face aging
W. Wang, Z. Cui, Y. Yan, J. Feng, S. Yan, X. Shu, and N. Sebe · 2016
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Ultra-resolving face images by discriminative generative networks
X. Yu and F. Porikli · 2016
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Energy-based generative adversarial network
J. Zhao, M. Mathieu, and Y. LeCun · 2016
Later among the works it cites.