Generative adversarial networks: Foundations and applications-Reference-Cited by-同舟云学术

Generative adversarial networks: Foundations and applications

Published:2018-05-01 Issue:3 Volume:39 Page:189-197
ISSN:1346-3969
Container-title:Acoustical Science and Technology
language:en
Short-container-title:Acoust. Sci. & Tech.

Author:

Kaneko Takuhiro¹

Affiliation:

1. NTT Communication Science Laboratories, NTT Corporation

Publisher

Acoustical Society of Japan

Subject

Acoustics and Ultrasonics

Link

https://www.jstage.jst.go.jp/article/ast/39/3/39_E183003/_pdf

Reference67 articles.

1. 1) T. Karras, T. Aila, S. Laine and J. Lehtinen, ``Progressive growing of GANs for improved quality, stability, and variation,'' arXiv preprint arXiv:1710.10196 (2017).

2. 2) S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele and H. Lee, ``Generative adversarial text to image synthesis,'' Proc. ICML 2016, pp. 1060-1069 (2016).

3. 3) H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang and D. Metaxas, ``StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks,'' Proc. ICCV 2017, pp. 5907-5915 (2017).

4. 4) S. E. Reed, Z. Akata, S. Mohan, S. Tenka, B. Schiele and H. Lee, ``Learning what and where to draw,'' Proc. NIPS 2016, pp. 217-225 (2016).

5. 5) T. Kaneko, K. Hiramatsu and K. Kashino, ``Generative attribute controller with conditional filtered generative adversarial networks,'' Proc. CVPR 2017, pp. 6089-6098 (2017).

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