Zero-Shot Text-to-Image Generation

Zero-Shot Text-to-Image Generation is a subtask in the field of Natural Language Processing, aiming to directly generate corresponding images from text descriptions without prior training on specific texts. The goal of this task is to utilize pre-trained models to achieve cross-modal transformation from text to image, generating high-quality, high-resolution images that are highly consistent with the text descriptions. Its application value lies in being able to quickly respond to diverse image generation needs, and it is widely used in creative design, virtual reality, and augmented reality fields.