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Generating and manipulating human facial images using high-level attributal controls are important and interesting problems.
Face description with local binary patterns: Application to face recognition
T. Ahonen, A. Hadid, and M. Pietikainen · 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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Attribute and simile classifiers for face verification
N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar · 2009
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Hierarchical ranking of facial attributes
A. Datta, R. Feris, and D. Vaquero · 2011
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Learning to share visual appearance for multiclass object detection
R. Salakhutdinov, A. Torralba, and J. Tenenbaum · 2011
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Robust face landmark estimation under occlusion
X. P. Burgos-Artizzu, P. Perona, and P. Dollár · 2013
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Learning multi-modal latent attributes
Y. Fu, T. M. Hospedales, T. Xiang, and S. Gong · 2013
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Attribute-based classification for zero-shot visual object categorization
C. H. Lampert, H. Nickisch, and S. Harmeling · 2013
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Joint cascade face detection and alignment
D. Chen, S. Ren, Y. Wei, X. Cao, and J. Sun · 2014
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Generative adversarial nets
I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, DavidWarde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Illumination-aware age progression
I. Kemelmacher-Shlizerman, S. Suwajanakorn, and S. M. Seitz · 2014
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Deep autoregressive networks
K.Gregor, I. Danihelka, A. Mnih, C.Blundell, and D.Wierstra · 2014
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learning to disentangle factors of variation with manifold interaction
S. Reed, K. Sohn, Y. Zhang, and H. Lee · 2014
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Deep learning face representation by joint identification-verification
Y. Sun, Y. Chen, X. Wang, and X. Tang · 2014
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Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Learning face representation from scratch
D. Yi, Z. Lei, S. Liao, and S. Z. Li · 2014
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Facial landmark detection by deep multi-task learning
Z. Zhang, P. Luo, C. C. Loy, and X. Tang · 2014
Cited alongside, same era.
Deep generative image models using a laplacian pyramid of adversarial networks
E. Denton, S. Chintala, A. Szlam, and R. Fergus · 2015
Cited alongside, same era.
learning to generate chairs with convolutional neural network
A. Dosovitskiy, J. T. Springenberg, M. Tatarchenko, and T. Brox · 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
Cited alongside, same era.
Deep convolutional inverse graphics network
T. Kulkarni, W.Whitney, P. Kohli, and J. Tenenbaum · 2015
Cited alongside, same era.
A convolutional neural network cascade for face detection
H. Li, Z. Lin, X. Shen, J. Brandt, and G. Hua · 2015
Cited alongside, same era.
Learning what and where to draw
S. Reed, Z. Akata, S. Mohan, S. Tenka, B. Schiele, and H. Lee · 2016
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Generative adversarial text-to-image synthesis
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee · 2016
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Moon:a mixed objective optimization network for the recognition of facial attributes
E. M. Rudd, M. Gunther, and T. E. Boult · 2016
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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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Learning structured output representation using deep conditional generative models
K. Sohn, X. Yan, and H. Lee · 2016
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conditional image generation with pixelcnn decoders
A. van den Oord, N. Kalchbrenner, O. Vinyals, L. Espeholt, A. Graves, and K. Kavukcuoglu · 2016
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Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
Cited alongside, same era.
Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Cited alongside, same era.
Generative image modeling using spatial lstms
L. Theis and M. Bethge · 2015
Cited alongside, same era.
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel · 2016
Cited alongside, same era.
Facial attributes classification using multi-task representation learning
M. Ehrlich, T. J. Shields, T. Almaev, and M. R. Amer · 2016
Cited alongside, same era.
Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sonderby, H. Larochelle, and OleWinther · 2016
Cited alongside, same era.
Later among the works it cites.
Walk and learn: Facial attribute representation learning from egocentric video and contextual data
J. Wang, Y. Cheng, and R. Feris · 2016
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A discriminative feature learning approach for deep face recognition
Y. Wen, K. Zhang, Z. Li, and Y. Qiao · 2016
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attribute2image: conditional image generation from visual attributes
X. Yan, J. Yang, K. Sohn, and H. Lee · 2016
Later among the works it cites.
Face attribute prediction using off-the-shelf cnn features
Y. Zhong, J. Sullivan, and H. Li · 2016
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View synthesis by appearance flow
T. Zhou, S. Tulsiani, W. Sun, J. Malik, and A. A. Efros · 2016
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Generative visual manipulation on the natural image manifold
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros · 2016
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Generative multi-adversarial networks
I. Durugkar, I. Gemp, and S. Mahadevan · 2017
Closest in time.
Stacked generative adversarial networks
X. Huang, Y. Li, O. Poursaeed, J. Hopcroft, and S. Belongie · 2017
Closest in time.
Learning residual images for face attribute manipulation
W. Shen and R. Liu · 2017
Closest in time.