Optimizing Prompts Using In-Context Few-Shot Learning for Text-to-Image Generative Models

Optimizing Prompts Using In-Context Few-Shot Learning for Text-to-Image Generative Models

Recently, various text-to-image generative models have been released, demonstrating their ability to generate high-quality synthesized images from text prompts. Despite these advancements, determining the appropriate text prompts to obtain desired images remains challenging. The quality of the synth...

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Bibliographic Details
Main Authors: Seunghun Lee, Jihoon Lee, Chan Ho Bae, Myung-Seok Choi, Ryong Lee, Sangtae Ahn
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
In-context few-shot learning
pretrained language model
prompt optimization
text-to-image generation
Online Access:https://ieeexplore.ieee.org/document/10378642/

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