GACnet-Text-to-Image Synthesis With Generative Models Using Attention Mechanisms With Contrastive Learning

GACnet-Text-to-Image Synthesis With Generative Models Using Attention Mechanisms With Contrastive Learning

The generation of high-quality images from textual descriptions is a challenging task in computer vision and natural language processing. The goal of text-to-image synthesis, a current topic of research, is to produce excellent images from written descriptions. This study proposes a hybrid approach...

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Bibliographic Details
Main Authors: Md. Ahsan Habib, Md. Anwar Hussen Wadud, Lubna Yeasmin Pinky, Mehedi Hasan Talukder, Mohammad Motiur Rahman, M. F. Mridha, Yuichi Okuyama, Jungpil Shin
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Text-to-image synthesis
generative adversarial networks
C-GAN
attention mechanism
contrastive learning technique
consistency
Online Access:https://ieeexplore.ieee.org/document/10360129/

Internet

https://ieeexplore.ieee.org/document/10360129/

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