Study on text-to-image generation method based on deep learning

With the continuous advancement of deep learning technology, text-generated images have emerged as a prominent research area. This paper proposes a deep learning-based approach for text image generation, utilizing a generative adversarial network (GAN) model to effectively convert textual descriptions into corresponding visual representations. Specifically, this study introduces a text-image fusion module that comprehensively integrates global and local features, ensuring the coherence of generated images. Experimental validation and comparison with other prevalent methods substantiate the exceptional performance, practicality, and potential applications of the proposed methodology.