Historical context & research account
DreamBooth fine-tunes a pretrained text-to-image model using a small set of subject images, associating a unique identifier with that subject. It brings preservation of identity into the generative process and supplies technical context for later customization of people, characters and products, as well as disputes concerning likeness.
Dates & version record
Date displayed for this node：2022-08-25 · Date recorded in the research master：2022-08-25
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Original sources & further reading
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DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
https://arxiv.org/abs/2208.12242
Current cited URL
Provenance, translation & verification
Archive node #094 · Historical node
Research masters & supplement references · 2
AI Art Genealogy Research Master · p. 28 · 094
Date as recorded: 2022-08-25
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation ↗
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
GenAI Visual Release Chronology Research Master · p. 8 · R034
Date as recorded: 2022-08-25
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation ↗
DreamBooth
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Cite this node
ANTI-AI ARCHIVE. DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation. Art-history node #094. https://salondesrefuses.cn/en/art-history/094
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