cGAN-based Manga Colorization Using a Single Training Image

The Japanese comic format known as Manga is popular all over the world. It is traditionally produced in black and white, and colorization is time consuming and costly. Automatic colorization methods generally rely on greyscale values, which are not present in manga. Furthermore, due to copyright protection, colorized manga available for training is scarce. We propose a manga colorization method based on conditional Generative Adversarial Networks (cGAN). Unlike previous cGAN approaches that use many hundreds or thousands of training images, our method requires only a single colorized reference image for training, avoiding the need of a large dataset. Colorizing manga using cGANs can produce blurry results with artifacts, and the resolution is limited. We therefore also propose a method of segmentation and color-correction to mitigate these issues. The final results are sharp, clear, and in high resolution, and stay true to the character's original color scheme.Comment: 8 pages, 13 figure

A survey of comics research in computer science

Graphical novels such as comics and mangas are well known all over the world. The digital transition started to change the way people are reading comics, more and more on smartphones and tablets and less and less on paper. In the recent years, a wide variety of research about comics has been proposed and might change the way comics are created, distributed and read in future years. Early work focuses on low level document image analysis: indeed comic books are complex, they contains text, drawings, balloon, panels, onomatopoeia, etc. Different fields of computer science covered research about user interaction and content generation such as multimedia, artificial intelligence, human-computer interaction, etc. with different sets of values. We propose in this paper to review the previous research about comics in computer science, to state what have been done and to give some insights about the main outlooks

"Normal" Feelings in "Abnormal" Worlds: On the Political Uses of Emotion in Science Fiction Manga

Scholars such as Darko Suvin have successfully argued for science fiction (SF) as fiction that portrays political alternatives through a focus on cognitive processes. This conception of SF minimizes the importance of character emotions, which has opened it to criticism from those who argue in favor of SF as a reflection of people’s wider psychological concerns. This dissertation argues that emotions, even when prominent within the narrative, can contribute directly to the cognitive exploration of political alternatives. If emotions are viewed not as a lack of overt logical reasoning but as a form of potential logic that can also provide alternative perspectives on the SF world, then it becomes possible to look at even emotion-heavy SF as sources of political ideas. This dissertation looks at how the depiction of emotions in SF manga (Japanese comics) affects the conveyance of political ideas. It shows that the portrayal of emotions in science fiction, even those which can be considered “commonplace” or “everyday”, can become political when sufficiently contextualized within alternative SF environments. Whether used to express political ideas or as a way to illuminate SF environments, emotion can expand the scope of possibilities for the exploration of political alternatives in SF.Netherlands Organization for Scientific Research NWOAsian Studie