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