Manuscript Number : IJSRSET184235

An Overview of GANs

Authors(2) :-Ketakee Nimavat, Tushar Champaneria

GANs are the most recent and exciting development in the field of generative models. Inspired by game theory, the system consists of two models which learn on its own. In this paper, the architecture of the models is explored along with its ideology. Research on application in GANs have shown improvement in various possible areas over the traditional models. Areas pertaining to image such as image filling, text to image are explored. Finally, the paper also discusses various open ended research areas that would help make GANs a more stable and optimal system.

Authors and Affiliations

Ketakee Nimavat
UG student, Computer Engineering Department, L. D. C. E, Ahmedabad, Gujarat, India
Tushar Champaneria
Assistant Professor, Computer Engineering Department, L. D. C. E, Ahmedabad, Gujarat, India

GANs, Image Processing, Generative models

  1. I. Goodfellow et al., "Generative Adversarial Nets," Adv. Neural Inf. Process. Syst. 27, pp. 2672-2680, 2014.
  2. P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros, "Image-to-Image Translation with Conditional Adversarial Networks," 2016.
  3. D. J. Im, C. D. Kim, H. Jiang, and R. Memisevic, "Generating images with recurrent adversarial networks," 2016.
  4. C. Ledig et al., "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network," 2016.
  5. S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee, "Generative Adversarial Text to Image Synthesis," Icml, pp. 1060-1069, 2016.
  6. H. Zhang et al., "StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks," 2016.
  7. A. Radford, L. Metz, and S. Chintala, "Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks," pp. 1-16, 2015.
  8. J. Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros, "Generative visual manipulation on the natural image manifold," Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 9909 LNCS, pp. 597-613, 2016.
  9. T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen, "Improved Techniques for Training GANs," pp. 1-10, 2016.

Publication Details

Published in : Volume 4 | Issue 2 | January-February 2018
Date of Publication : 2018-01-20
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 214-217
Manuscript Number : IJSRSET184235
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Ketakee Nimavat, Tushar Champaneria, " An Overview of GANs, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 2, pp.214-217, January-February-2018.
Journal URL : http://ijsrset.com/IJSRSET184235

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