  Neural style transfer (NST) can create impressive artworks by transferring
reference style to content image. Current image-to-image NST methods are short
of fine-grained controls, which are often demanded by artistic editing. To
mitigate this limitation, we propose a drawing-like interactive style transfer
(IST) method, by which users can interactively create a harmonious-style image.
Our IST method can serve as a brush, dip style from anywhere, and then paint to
any region of the target content image. To determine the action scope, we
formulate a fluid simulation algorithm, which takes styles as pigments around
the position of brush interaction, and diffusion in style or content images
according to the similarity maps. Our IST method expands the creative dimension
of NST. By dipping and painting, even employing one style image can produce
thousands of eye-catching works. The demo video is available in supplementary
files or in http://mmcheng.net/ist.
