  Style transfer has been widely applied to give real-world images a new
artistic look. However, given a stylized image, the attempts to use typical
style transfer methods for de-stylization or transferring it again into another
style usually lead to artifacts or undesired results. We realize that these
issues are originated from the content inconsistency between the original image
and its stylized output. Therefore, in this paper we advance to keep the
content information of the input image during the process of style transfer by
the power of steganography, with two approaches proposed: a two-stage model and
an end-to-end model. We conduct extensive experiments to successfully verify
the capacity of our models, in which both of them are able to not only generate
stylized images of quality comparable with the ones produced by typical style
transfer methods, but also effectively eliminate the artifacts introduced in
reconstructing original input from a stylized image as well as performing
multiple times of style transfer in series.
