DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation. (arXiv:2208.12242v1 [cs.CV])

Large text-to-image models achieved a remarkable leap in the evolution of AI,
enabling high-quality and diverse synthesis of images from a given text prompt.
However, these models lack the ability to mimic the appearance of subjects in a
given reference set and synthesize novel renditions of them in different
contexts. In this work, we present a new approach for "personalization" of
text-to-image diffusion models (specializing them to users' needs). Given as
input just a few images of a subject, we …

arxiv cv diffusion diffusion models generation image text text-to-image