Text-to-image generation using GAN

Kesham, Ganesh (2024) Text-to-image generation using GAN. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research delves into the pursuit of generating realistic images from textual descriptions, a compelling yet challenging task within current AI systems. While existing technologies fall short of this goal, recent advancements in recurrent neural networks have demonstrated proficiency in learning discriminative text features. Additionally, deep convolutional generative adversarial networks (GANs) have shown promise in generating highly realistic images across specific categories like faces, album covers, and interiors. In this study, I introduce a novel deep architecture and GAN formulation aimed at bridging these text and image modelling advancements. Here approach is centered on translating textual concepts into vivid visual representations, effectively converting characters into pixelated images. Through rigorous experimentation, we showcase the capability of our model to produce credible images of birds and flowers from intricate textual descriptions. This work represents a significant step toward achieving the synthesis of detailed images solely from text, offering insights into the convergence of text and image modelling within the realm of artificial intelligence.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Syed, Muslim Jameel UNSPECIFIED
Uncontrolled Keywords:	Text-to-Image Generation; Generative Adversarial Networks (GANs); Image Synthesis
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Tamara Malone
Date Deposited:	04 Apr 2025 15:04
Last Modified:	04 Apr 2025 15:04
URI:	https://norma.ncirl.ie/id/eprint/7368

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