Exploring Progress in Text-to-Image Synthesis: An In-Depth Survey on the Evolution of Generative Adversarial Networks

Md Ahsan Habib; Md Anwar Hussen Wadud; Md Fazlul Karim Patwary; Mohammad Motiur Rahman; M. F. Mridha; Yuichi Okuyama; Jungpil Shin

doi:10.1109/access.2024.3435541

journal article Open Access Jan 01, 2024

Exploring Progress in Text-to-Image Synthesis: An In-Depth Survey on the Evolution of Generative Adversarial Networks

Md Ahsan Habib

Md Anwar Hussen Wadud

Md Fazlul Karim Patwary

Mohammad Motiur Rahman

M. F. Mridha

Yuichi Okuyama

Jungpil Shin

IEEE Access Vol. 12 pp. 178401-178440 · Institute of Electrical and Electronics Engineers (IEEE)

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Details

Published: Jan 01, 2024
Vol/Issue: 12
Pages: 178401-178440
License: View

Authors

M

Md Ahsan Habib

Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh

M

Md Anwar Hussen Wadud

Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh

M

Md Fazlul Karim Patwary

Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, Bangladesh

M

Mohammad Motiur Rahman

Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh

M

M. F. Mridha

Department of Computer Science, American International University-Bangladesh, Dhaka, Bangladesh

Y

Yuichi Okuyama

School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

J

Jungpil Shin

School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

Funding

Competitive Research Fund of The University of Aizu, Japan

Cite This Article

Md Ahsan Habib, Md Anwar Hussen Wadud, Md Fazlul Karim Patwary, et al. (2024). Exploring Progress in Text-to-Image Synthesis: An In-Depth Survey on the Evolution of Generative Adversarial Networks. IEEE Access, 12, 178401-178440. https://doi.org/10.1109/access.2024.3435541

Exploring Progress in Text-to-Image Synthesis: An In-Depth Survey on the Evolution of Generative Adversarial Networks

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