Text Image

Text-image research focuses on understanding and generating images containing text, aiming to improve the accuracy, realism, and diversity of such images. Current research heavily utilizes diffusion models, often enhanced with techniques like glyph-aware training and dual translation learning, to address challenges such as legible text generation, multi-concept synthesis, and cross-lingual capabilities. This field is significant for applications in combating misinformation (detecting text-image inconsistencies), improving scene text recognition, and enabling novel image editing and generation tasks, ultimately advancing both computer vision and natural language processing.