Sketch2Manga: Shaded Manga Screening from Sketch with Diffusion Models

Fuente: arXiv
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Autori principali: Lin, Jian, Liu, Xueting, Li, Chengze, Xie, Minshan, Wong, Tien-Tsin
Natura: Preprint
Pubblicazione: 2024
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_version_ 1866914712944377856
author Lin, Jian
Liu, Xueting
Li, Chengze
Xie, Minshan
Wong, Tien-Tsin
author_facet Lin, Jian
Liu, Xueting
Li, Chengze
Xie, Minshan
Wong, Tien-Tsin
contents 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 of generating high-quality shaded high-frequency screentones. The classic manga screening approaches generally require user input to provide screentone exemplars or a reference manga image. The recent deep learning models enables the 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_08266
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sketch2Manga: Shaded Manga Screening from Sketch with Diffusion Models
Lin, Jian
Liu, Xueting
Li, Chengze
Xie, Minshan
Wong, Tien-Tsin
Computer Vision and Pattern Recognition
Graphics
I.4.6; I.3.3; I.3.8
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 of generating high-quality shaded high-frequency screentones. The classic manga screening approaches generally require user input to provide screentone exemplars or a reference manga image. The recent deep learning models enables the 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.
title Sketch2Manga: Shaded Manga Screening from Sketch with Diffusion Models
topic Computer Vision and Pattern Recognition
Graphics
I.4.6; I.3.3; I.3.8
url https://arxiv.org/abs/2403.08266