@Article{cmes.2022.018201,
AUTHOR = {Jong-In Choi, Soo-Kyun Kim, Shin-Jin Kang},
TITLE = {Image Translation Method for Game Character Sprite Drawing},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {131},
YEAR = {2022},
NUMBER = {2},
PAGES = {747--762},
URL = {http://www.techscience.com/CMES/v131n2/47001},
ISSN = {1526-1506},
ABSTRACT = {Two-dimensional (2D) character animation is one of the most important visual elements on which users’ interest
is focused in the game field. However, 2D character animation works in the game field are mostly performed
manually in two dimensions, thus generating high production costs. This study proposes a generative adversarial
network based production tool that can easily and quickly generate the sprite images of 2D characters. First, we
proposed a methodology to create a synthetic dataset for training using images from the real world in the game
resource production field where machine learning datasets are insufficient. In addition, we have enabled effective
sprite generation while minimizing user input in the process of using the tool. To this end, we proposed a mixed
input method with a small number of segmentations and skeletal bone paintings. The proposed image-to-image
translation network effectively generated sprite images from the user input images using the skeletal loss. We
conducted an experiment regarding the number of images required and showed that 2D sprite resources can be
generated even with a small number of segmentation inputs and one skeletal bone drawing.},
DOI = {10.32604/cmes.2022.018201}
}