DeepAI AI Chat
Log In Sign Up

Painting Style-Aware Manga Colorization Based on Generative Adversarial Networks

by   Yugo Shimizu, et al.

Japanese comics (called manga) are traditionally created in monochrome format. In recent years, in addition to monochrome comics, full color comics, a more attractive medium, have appeared. Unfortunately, color comics require manual colorization, which incurs high labor costs. Although automatic colorization methods have been recently proposed, most of them are designed for illustrations, not for comics. Unlike illustrations, since comics are composed of many consecutive images, the painting style must be consistent. To realize consistent colorization, we propose here a semi-automatic colorization method based on generative adversarial networks (GAN); the method learns the painting style of a specific comic from small amount of training data. The proposed method takes a pair of a screen tone image and a flat colored image as input, and outputs a colorized image. Experiments show that the proposed method achieves better performance than the existing alternatives.


page 6

page 7


Feature Statistics Mixing Regularization for Generative Adversarial Networks

In generative adversarial networks, improving discriminators is one of t...

cGAN-based Manga Colorization Using a Single Training Image

The Japanese comic format known as Manga is popular all over the world. ...

SLGAN: Style- and Latent-guided Generative Adversarial Network for Desirable Makeup Transfer and Removal

There are five features to consider when using generative adversarial ne...

Generative-Adversarial-Networks-based Ghost Recognition

Nowadays, target recognition technique plays an important role in many f...

Generative Adversarial Networks for photo to Hayao Miyazaki style cartoons

This paper takes on the problem of transferring the style of cartoon ima...

Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments

GANs (Generative adversarial networks) is a new AI technology that can p...

Towards Vivid and Diverse Image Colorization with Generative Color Prior

Colorization has attracted increasing interest in recent years. Classic ...