People who use AI text-to-image generator like ChatGPT or Google Gemini often encounter a maddening problem: the image looks nearly perfect, but when you ask the AI to fix one small detail, it messes up something unrelated. The issue is caused by the way most state-of-the-art image generators are built using a diffusion model in latent space, meaning they compress concepts such as a cat or a dog into their essential details and store them so they can be retrieved quickly and efficiently when it’s time to create an image. Researchers at the University of Rochester and NVIDIA created a pixel-space diffusion model that allows users to make precise changes to individual pixels without unintentionally altering other details . News summary: https://www.rochester.edu/newscenter/how-to-fix-ai-generated-images-pixel-by-pixel-728132/ Research paper: https://doi.org/10.48550/arXiv.2609.24919 GitHub: https://pixeldit.github.io/pixeldit2/ submitted by /u/URochester_Hajim
Originally posted by u/URochester_Hajim on r/ArtificialInteligence