Text to Image

Text-to-image synthesis aims to generate realistic images from textual descriptions, leveraging advancements in deep learning, particularly diffusion models and large language models. Current research emphasizes improving image quality, addressing biases and safety concerns (e.g., generating inappropriate content), and enhancing control over generated images through techniques like prompt engineering and embedding optimization. This field is significant for its potential applications in various domains, including creative design, 3D modeling, and content creation, while also raising important ethical considerations regarding bias and responsible AI development.