Syntheses of Dual-Artistic Media Effects Using a Generative Model with Spatial Control

We present a generative model with spatial control to synthesize dual-artistic media effects. It generates different artistic media effects on the foreground and background of an image. In order to apply a distinct artistic media effect to a photograph, deep learning-based models require a training dataset composed of pairs of a photograph and its corresponding artwork images. To build the dataset, we apply some existing techniques that generate an artwork image including colored pencil, watercolor and abstraction from a photograph. In order to produce a dual artistic effect, we apply a semantic segmentation technique to separate the foreground and background of a photograph. Our model applies different artistic media effects on the foreground and background using space control module such as SPADE block.