An Overview of GANs

Authors

  • 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

Keywords:

GANs, Image Processing, Generative models

Abstract

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.

References

  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.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-01-20

Issue

Volume 4, Issue 2, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
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.