Automatic line art colorization has been largely adapted to the anime industry since it can improve animation production. Reference-based method provides a more convenient and intuitive method but now is equipped with a challenge in aspects of color match and semantic consistency. In this paper, we propose an GAN-based line art colorization architecture. We introduce an attention mechanism module which fuses and merges coordinate attention and stop-gradient attention for improving encoder's ability of key region perception and feature extraction. To alleviate color overflow, we design a segmentation branch to control the region correspondence between the line art and the reference image. Multiple experiments unequivocally illustrate that our method excels over other state-of-the-art reference-based techniques in animation line art colorization task.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.