Fetching the paper…
Reading the bibliography…
Automatic image synthesis research has been rapidly growing with deep networks getting more and more expressive.
Signature verification using a ”siamese” time delay neural network
J. Bromley, I. Guyon, Y. LeCun, E. Säckinger, and R. Shah · 1994
Earlier work this paper cites.
Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, and Y. LeCun · 2005
Earlier work this paper cites.
Photo clip art
J.-F. Lalonde, D. Hoiem, A. A. Efros, C. Rother, J. Winn, and A. Criminisi · 2007
Earlier work this paper cites.
Labelme: A database and web-based tool for image annotation
B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman · 2008
Earlier work this paper cites.
Nonparametric scene parsing via label transfer
C. Liu, J. Yuen, and A. Torralba · 2011
Earlier work this paper cites.
Rectifier nonlinearities improve neural network acoustic models
A. L. Maas, A. Y. Hannun, and A. Y. Ng · 2013
Earlier work this paper cites.
Superparsing: Scalable nonparametric image parsing with superpixels
J. Tighe and S. Lazebnik · 2013
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
Earlier work this paper cites.
Transient attributes for high-level understanding and editing of outdoor scenes
P.-Y. Laffont, Z. Ren, X. Tao, C. Qian, and J. Hays · 2014
Earlier work this paper cites.
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 networks
A. Dosovitskiy, J. Springenberg, and T.Brox · 2015
Cited alongside, same era.
Draw: A recurrent neural network for image generation
K. Gregor, I. Danihelka, A. Graves, D. Rezende, and D. Wierstra · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Deep convolutional inverse graphics network
T. D. Kulkarni, W. F. Whitney, P. Kohli, and J. Tenenbaum · 2015
Cited alongside, same era.
Empirical evaluation of rectified activations in convolutional network
B. Xu, N. Wang, T. Chen, and M. Li · 2015
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2016
Closest in time.
Learning what and where to draw
S. Reed, Z. Akata, S. Mohan, S. Tenka, B. Schiele, and H. Lee · 2016
Closest in time.
Generative adversarial text to image synthesis
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee · 2016
Closest in time.
Pixel recurrent neural networks
A. van den Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
Closest in time.
Generating videos with scene dynamics
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
Closest in time.
Generative image modeling using style and structure adversarial networks
X. Wang and A. Gupta · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
The cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
Cited alongside, same era.
Coupled generative adversarial networks
M. Liu and O. Tuzel · 2016
Cited alongside, same era.
Generating images from captions with attention
E. Mansimov, E. Parisotto, L. J. Ba, and R. Salakhutdinov · 2016
Cited alongside, same era.
Conditional image generation with pixelcnn decoders
A. v. d. Oord, N. Kalchbrenner, O. Vinyals, L. Espeholt, A. Graves, and K. Kavukcuoglu · 2016
Cited alongside, same era.
A Fast Method for Estimating Transient Scene Attributes
R. Baltenberger, M. Zhai, C. Greenwell, S. Workman, and N. Jacobs
Cited in the paper.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum · 2016
Closest in time.
Attribute2image: Conditional image generation from visual attributes
X. Yan, J. Yang, K. Sohn, and H. Lee · 2016
Closest in time.
Semantic understanding of scenes through the ADE20K dataset
B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso, and A. Torralba · 2016
Closest in time.
Generative visual manipulation on the natural image manifold
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros · 2016
Closest in time.