SKETCH2MANGA: Shaded Manga Screening from Sketch with Diffusion Models

While manga is a popular entertainment form, creating manga is tedious, especially adding screentones to the created sketch, namely manga screening. Unfortunately, there is no existing method that tailors for automatic manga screening, probably due to the difficulty in generating shaded high-frequency screentones of high-quality. Classic manga screening approaches generally require user input to provide screentone exemplars or a reference manga image. Recent deep learning models enable automatic generation by learning from a large-scale dataset. However, the state-of-the-art models still fail to generate high-quality shaded screentones due to the lack of a tailored model and high-quality manga training data. In this paper, we propose a novel sketch-to-manga framework that first generates a color illustration from the sketch and then generates a screentoned manga based on the intensity guidance. Our method significantly outperforms existing methods in generating high-quality manga with shaded high-frequency screentones.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10647842
Citations
5
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
1.25
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article

SKETCH2MANGA: Shaded Manga Screening from Sketch with Diffusion Models

Tien‐Tsin Wong, Chengze Li, Xueting Liu, Minshan Xie et al.
5 citations
Handwritten Text Recognition Techniques
1.25
article

SKETCH2MANGA: Shaded Manga Screening from Sketch with Diffusion Models

Tien‐Tsin Wong, Chengze Li, Xueting Liu, Minshan Xie, Jian Lin
article en
5 citations

Abstract

While manga is a popular entertainment form, creating manga is tedious, especially adding screentones to the created sketch, namely manga screening. Unfortunately, there is no existing method that tailors for automatic manga screening, probably due to the difficulty in generating shaded high-frequency screentones of high-quality. Classic manga screening approaches generally require user input to provide screentone exemplars or a reference manga image. Recent deep learning models enable automatic generation by learning from a large-scale dataset. However, the state-of-the-art models still fail to generate high-quality shaded screentones due to the lack of a tailored model and high-quality manga training data. In this paper, we propose a novel sketch-to-manga framework that first generates a color illustration from the sketch and then generates a screentoned manga based on the intensity guidance. Our method significantly outperforms existing methods in generating high-quality manga with shaded high-frequency screentones.

Chinese University of Hong Kong (HK), Saint Francis University (US), Monash University (AU)
Openalex Percentile: Top 19%
Handwritten Text Recognition Techniques
1.25
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SKETCH2MANGA: Shaded Manga Screening from Sketch with Diffusion Models — Tien‐Tsin Wong, Chengze Li, et al. · (2024) | TGRS Research Map | TGRS