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2025-12-18 12:20:26
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DreamBooth DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation Nataniel Ruiz Yuanzhen Li Varun Jampani Yael Pritch Michael Rubinstein Kfir Aberman Google Research It’s like a photo booth, but once the subject is captured, it can be synthesized wherever your dreams take you… [Paper] ( new! ) [Dataset] [BibTeX] Abstract 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 fine-tune a pretrained text-to-image model (Imagen, although our method is not limited to a specifi...
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