2018

Self-Attention Generative Adversarial Networks

Zhang, Han, Goodfellow, Ian, Metaxas, Dimitris et al.

Understand

In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks.

Traditional convolutional GANs generate high-resolution details as a function of only spatially local points in lower-resolution feature maps.
In SAGAN, details can be generated using cues from all feature locations.
Moreover, the discriminator can check that highly detailed features in distant portions of the image are consistent with each other.

Built on

HYPE: human eye perceptual evaluation of generative models
Original
Zhou, S., Gordon, M., Krishna, R., Narcomey, A., Morina, D., and Bernstein, M. S · 1904
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Original
Bahdanau, D., Cho, K., and Bengio, Y · 2014
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A. C., and Bengio, Y · 2014
Earlier work this paper cites.
DRAW: A recurrent neural network for image generation
Gregor, K., Danihelka, I., Graves, A., Rezende, D. J., and Wierstra, D · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
Earlier work this paper cites.
ImageNet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., and Fei-Fei, L · 2015
Earlier work this paper cites.
Show, attend and tell: Neural image caption generation with visual attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A. C., Salakhutdinov, R., Zemel, R. S., and Bengio, Y · 2015
Earlier work this paper cites.
Long short-term memory-networks for machine reading
Cheng, J., Dong, L., and Lapata, M · 2016
Earlier work this paper cites.
Coupled generative adversarial networks
Liu, M. and Tuzel, O · 2016
Earlier work this paper cites.
Faster asynchronous sgd
Original
Odena, A · 2016
Earlier work this paper cites.
A decomposable attention model for natural language inference
Parikh, A. P., Täckström, O., Das, D., and Uszkoreit, J · 2016
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., and Chintala, S · 2016
Earlier work this paper cites.
Improved techniques for training GANs
Salimans, T., Goodfellow, I. J., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
Earlier work this paper cites.
Stacked attention networks for image question answering
Yang, Z., He, X., Gao, J., Deng, L., and Smola, A. J · 2016
Earlier work this paper cites.
Wasserstein GAN
Original
Arjovsky, M., Chintala, S., and Bottou, L · 2017
Earlier work this paper cites.
Mode regularized generative adversarial networks
Che, T., Li, Y., Jacob, A. P., Bengio, Y., and Li, W · 2017
Earlier work this paper cites.
Improved training of wasserstein GANs
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
Earlier work this paper cites.

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