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Investigating Prompt Engineering in Diffusion Models
November 21, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Sam Witteveen, Martin Andrews
arXiv ID
2211.15462
Category
cs.CV: Computer Vision
Cross-listed
cs.AI,
cs.CL
Citations
80
Venue
arXiv.org
Last Checked
5 months ago
Abstract
With the spread of the use of Text2Img diffusion models such as DALL-E 2, Imagen, Mid Journey and Stable Diffusion, one challenge that artists face is selecting the right prompts to achieve the desired artistic output. We present techniques for measuring the effect that specific words and phrases in prompts have, and (in the Appendix) present guidance on the selection of prompts to produce desired effects.
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