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research-article

PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation

Authors:

Yingchaojie Feng,

Wei ChenAuthors Info & Claims

IEEE Transactions on Visualization and Computer Graphics, Volume 30, Issue 1

Pages 295 - 305

https://doi.org/10.1109/TVCG.2023.3327168

Published: 01 January 2024 Publication History

Abstract

Generative text-to-image models have gained great popularity among the public for their powerful capability to generate high-quality images based on natural language prompts. However, developing effective prompts for desired images can be challenging due to the complexity and ambiguity of natural language. This research proposes <italic>PromptMagician</italic>, a visual analysis system that helps users explore the image results and refine the input prompts. The backbone of our system is a prompt recommendation model that takes user prompts as input, retrieves similar prompt-image pairs from DiffusionDB, and identifies special (important and relevant) prompt keywords. To facilitate interactive prompt refinement, <italic>PromptMagician</italic> introduces a multi-level visualization for the cross-modal embedding of the retrieved images and recommended keywords, and supports users in specifying multiple criteria for personalized exploration. Two usage scenarios, a user study, and expert interviews demonstrate the effectiveness and usability of our system, suggesting it facilitates prompt engineering and improves the creativity support of the generative text-to-image model.

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Cited By

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PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation

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cover image IEEE Transactions on Visualization and Computer Graphics

IEEE Transactions on Visualization and Computer Graphics Volume 30, Issue 1

Jan. 2024

1456 pages

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1077-2626 © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 01 January 2024

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Cited By

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https://dl.acm.org/doi/10.1145/3694681
Zhou MZhang DYou WYu ZWu YPan CLiu HLao TChen P(2024)StyleFactory: Towards Better Style Alignment in Image Creation through Style-Strength-Based Control and EvaluationProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676370(1-15)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676370
Wang ZHuang YSong DMa LZhang T(2024)PromptCharm: Text-to-Image Generation through Multi-modal Prompting and RefinementProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642803(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642803
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