Reference-based attention mechanism and region segmentation line art colorization

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.