ShadowMagic: Designing Human-AI Collaborative Support for Comic Professionals’ Shadowing

Shadowing allows artists to convey realistic volume and emotion of characters in comic colorization. While AI technologies have the potential to improve professionals’ shadowing experience, current practice is manual and time-consuming. To understand how we can improve their shadowing experience, we conducted interviews with 5 professionals. We found that professionals’ level of engagement can vary depending on semantics, such as characters’ faces or hair. We also found they spent time on shadow “landscaping”—deciding where to put big shadow regions to make a realistic volumetric presentation—while the final results can dramatically vary depending on their “staging” and “attention guiding” needs. We found they would accept AI suggestions for less engaging semantic parts or landscaping, while they would need to have the capability to adjust details. Based on our observations, we built ShadowMagic that (1) generates AI-driven shadows based on typically used light directions, (2) enables a user to selectively choose the results depending on the semantics, and (3) allows users to finish shadow areas by themselves for further perfection. Through a summative evaluation with 5 professionals, we found that they were significantly more satisfied with our AI-driven results than a baseline. We also found ShadowMagic’s “step by step” workflow helps participants more easily adopt AI-driven results. We conclude by providing implications.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676332
Citations
5
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
1.74
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article

ShadowMagic: Designing Human-AI Collaborative Support for Comic Professionals’ Shadowing

C.-W. Yan, Yoon Kiheon, Yotam Gingold, Sung-Soo Hong et al.
5 citations
Artificial Intelligence in Games
1.74
article

ShadowMagic: Designing Human-AI Collaborative Support for Comic Professionals’ Shadowing

C.-W. Yan, Yoon Kiheon, Yotam Gingold, Sung-Soo Hong, Amrita Ganguly, John Joon Young Chung, Tong Sun
article en
5 citations

Abstract

Shadowing allows artists to convey realistic volume and emotion of characters in comic colorization. While AI technologies have the potential to improve professionals’ shadowing experience, current practice is manual and time-consuming. To understand how we can improve their shadowing experience, we conducted interviews with 5 professionals. We found that professionals’ level of engagement can vary depending on semantics, such as characters’ faces or hair. We also found they spent time on shadow “landscaping”—deciding where to put big shadow regions to make a realistic volumetric presentation—while the final results can dramatically vary depending on their “staging” and “attention guiding” needs. We found they would accept AI suggestions for less engaging semantic parts or landscaping, while they would need to have the capability to adjust details. Based on our observations, we built ShadowMagic that (1) generates AI-driven shadows based on typically used light directions, (2) enables a user to selectively choose the results depending on the semantics, and (3) allows users to finish shadow areas by themselves for further perfection. Through a summative evaluation with 5 professionals, we found that they were significantly more satisfied with our AI-driven results than a baseline. We also found ShadowMagic’s “step by step” workflow helps participants more easily adopt AI-driven results. We conclude by providing implications.

George Mason University (US), Pusan National University (KR)
Openalex Percentile: Top 13%
Artificial Intelligence in Games
1.74
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