Research issues on generative adversarial networks and applications

Toshpulatov Mukhiddin; Wookey Lee; Suan Lee; Tojiboev Rashid

doi:10.1109/BigComp48618.2020.00-19

Research issues on generative adversarial networks and applications

Toshpulatov Mukhiddin, Wookey Lee, Suan Lee, Tojiboev Rashid

Inha University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

Generative Adversarial Networks introduces a challenging problem in the field of image generation and computer vision. Generating especially 3D face images is becoming very significant and difficult. This is openings in many interesting applications including Virtual Reality, Augmented Reality, Computer games, teleconferencing, Virtual try-on, Special effect, and so on. This paper contains three sections. The first section describes the Generative Adversarial Networks. The second section describes applications and methods and finally, the last section describes the future research directions of Generative Adversarial Networks.

Original language	English
Title of host publication	Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020
Editors	Wookey Lee, Luonan Chen, Yang-Sae Moon, Julien Bourgeois, Mehdi Bennis, Yu-Feng Li, Young-Guk Ha, Hyuk-Yoon Kwon, Alfredo Cuzzocrea
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	487-488
Number of pages	2
ISBN (Electronic)	9781728160344
DOIs	https://doi.org/10.1109/BigComp48618.2020.00-19
State	Published - Feb 2020
Event	2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020 - Busan, Korea, Republic of Duration: 19 Feb 2020 → 22 Feb 2020

Publication series

Name	Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020

Conference

Conference	2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020
Country/Territory	Korea, Republic of
City	Busan
Period	19/02/20 → 22/02/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

3D-face-generation
Deep-learning
Deep-neural-network
Generative-Adversarial-Networks
Generator

Access to Document

10.1109/BigComp48618.2020.00-19

Cite this

Mukhiddin, T., Lee, W., Lee, S., & Rashid, T. (2020). Research issues on generative adversarial networks and applications. In W. Lee, L. Chen, Y.-S. Moon, J. Bourgeois, M. Bennis, Y.-F. Li, Y.-G. Ha, H.-Y. Kwon, & A. Cuzzocrea (Eds.), Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020 (pp. 487-488). Article 9070385 (Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigComp48618.2020.00-19

Mukhiddin, Toshpulatov ; Lee, Wookey ; Lee, Suan et al. / Research issues on generative adversarial networks and applications. Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020. editor / Wookey Lee ; Luonan Chen ; Yang-Sae Moon ; Julien Bourgeois ; Mehdi Bennis ; Yu-Feng Li ; Young-Guk Ha ; Hyuk-Yoon Kwon ; Alfredo Cuzzocrea. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 487-488 (Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020).

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abstract = "Generative Adversarial Networks introduces a challenging problem in the field of image generation and computer vision. Generating especially 3D face images is becoming very significant and difficult. This is openings in many interesting applications including Virtual Reality, Augmented Reality, Computer games, teleconferencing, Virtual try-on, Special effect, and so on. This paper contains three sections. The first section describes the Generative Adversarial Networks. The second section describes applications and methods and finally, the last section describes the future research directions of Generative Adversarial Networks.",

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Mukhiddin, T, Lee, W, Lee, S & Rashid, T 2020, Research issues on generative adversarial networks and applications. in W Lee, L Chen, Y-S Moon, J Bourgeois, M Bennis, Y-F Li, Y-G Ha, H-Y Kwon & A Cuzzocrea (eds), Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020., 9070385, Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020, Institute of Electrical and Electronics Engineers Inc., pp. 487-488, 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020, Busan, Korea, Republic of, 19/02/20. https://doi.org/10.1109/BigComp48618.2020.00-19

Research issues on generative adversarial networks and applications. / Mukhiddin, Toshpulatov; Lee, Wookey; Lee, Suan et al.
Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020. ed. / Wookey Lee; Luonan Chen; Yang-Sae Moon; Julien Bourgeois; Mehdi Bennis; Yu-Feng Li; Young-Guk Ha; Hyuk-Yoon Kwon; Alfredo Cuzzocrea. Institute of Electrical and Electronics Engineers Inc., 2020. p. 487-488 9070385 (Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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BT - Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020

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A2 - Ha, Young-Guk

A2 - Kwon, Hyuk-Yoon

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020

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ER -

Mukhiddin T, Lee W, Lee S, Rashid T. Research issues on generative adversarial networks and applications. In Lee W, Chen L, Moon YS, Bourgeois J, Bennis M, Li YF, Ha YG, Kwon HY, Cuzzocrea A, editors, Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 487-488. 9070385. (Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020). doi: 10.1109/BigComp48618.2020.00-19

Research issues on generative adversarial networks and applications

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this