• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.75-86
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• 2008

Black/white comic rendering is one of the researches in the field of non-photorealistic rendering(NPR). Black/white comics have been produced manually as yet. But these previous systems require lots of time and manual work. So we propose the COmics Rendering system on VIdeo Stream (CORVIS) which transforms video streams into black/white comic cuts. Stylized font, one of comic representations, can be used to express onomatopoeic words and mimetic dialogue exaggeratively. But current comic generation systems do not provide enough effects of stylized font. This paper proposes a model for stylized fonts to express various effects. Effects of stylized fonts we proposed include geometric deformations. Thus we could represent stylized fonts on the still cut of movies and the background texture on a cuts of plain black/white comics. The final quality of our system produced is good enough to compare with manual black/white comics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.