Generative AI programs can generate images from textual prompts. These models work best when they generate images of single objects. Creating complete scenes is still difficult. Michael Ying Yang, a UT-researcher from the faculty of ITC recently developed a novel method that can graph scenes from images that can serve as a blueprint for generating realistic and coherent images. He and his team recently published their findings in the journal IEEE Transactions on Pattern Analysis and Machine Intelligence.