Historical context & research account
AnimateDiff introduces motion modelling as a pluggable component within personalized text-to-image diffusion systems. Existing character models, styles and community assets can participate in animated outputs. This extends generation from still images toward video while retaining parts of the earlier image-model ecosystem.
Dates & version record
Date displayed for this node：2023 · Date recorded in the research master：2023
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Original sources & further reading
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AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
https://arxiv.org/abs/2307.04725
Current cited URL
Provenance, translation & verification
Archive node #106 · Historical node
Research masters & supplement references · 2
AI Art Genealogy Research Master · p. 31 · 106
Date as recorded: 2023
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning ↗
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
GenAI Visual Release Chronology Research Master · p. 18 · R091
Date as recorded: 2023
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning ↗
AnimateDiff
Archive account adapted from the masters, not a full translation of the linked work. AI-assisted translation; human review pending.
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Cite this node
ANTI-AI ARCHIVE. AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning. Art-history node #106. https://salondesrefuses.cn/en/art-history/106
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