Grayscale Image Colorization with GAN and CycleGAN in Different Image
  Domain
Chen Liang Yunchen Sheng Yichen Mo
Automatic colorization of grayscale image has been a challenging task.
Previous research have applied supervised methods in conquering this problem [
1]. In this paper, we reproduces a GAN-based coloring model, and experiments
one of its variant. We also proposed a CycleGAN based model and experiments
those methods on various datasets. The result shows that the proposed CycleGAN
model does well in human-face coloring and comic coloring, but lack the ability
to diverse colorization.