人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
原著論文
事前学習済み大規模画像生成モデルを用いた中空構造アイコン線画彩色
宮内 洸希折原 良平清 雄一田原 康之大須賀 昭彦
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2024 年 39 巻 6 号 p. AG24-E_1-11

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Icons are utilized to visually elucidate functions and objects, and are frequently employed on websites. Forweb developers with limited design skills, producing a substantial volume of icons poses a challenge. Consequently,there is a demand for automated methods to generate icons. The process of creating icons involves two stages: linedrawing and coloring. Recent research on automating the coloring process through deep learning has been active.However, existing methods fail to recognize the entities represented by line drawings, leading to inaccuracies inreflecting the target’s structure during the coloring process. A notable limitation of these methods is their inability toaccurately color line drawings of icons with hollow structures, such as donuts. In this study, we introduce a method forcoloring hollowed-out icons, ensuring adherence to the original line drawings. Specifically, we employ a large-scalepre-trained model to generate icons from line drawings, supplemented by reference images and textual descriptions.To facilitate experimental implementation, we compiled a dataset comprising gradient style icons and their associatedtexts. The results of our experimental evaluation indicate that our method surpasses existing approaches in morethan one metrics. Furthermore, the outcomes of the coloring experiments reveal that our method faces challenges incoloring efficiency and highlight the limitations of incorporating text as an auxiliary input for the coloring process.

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© JSAI (The Japanese Society for Artificial Intelligence)
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