Text-to-Image Generation involves using advanced models to convert textual descriptions into visual images. Techniques often leverage models like GANs (Generative Adversarial Networks) which learn to generate photorealistic images from text prompts. An example is DALL-E, which creates detailed images from text like "an astronaut riding a horse in space." It's closely related to fields like Natural Language Processing and Computer Vision as it combines understanding text with generating visuals.