  We present a novel image editing system that generates images as the user
provides free-form mask, sketch and color as an input. Our system consist of a
end-to-end trainable convolutional network. Contrary to the existing methods,
our system wholly utilizes free-form user input with color and shape. This
allows the system to respond to the user's sketch and color input, using it as
a guideline to generate an image. In our particular work, we trained network
with additional style loss which made it possible to generate realistic
results, despite large portions of the image being removed. Our proposed
network architecture SC-FEGAN is well suited to generate high quality synthetic
image using intuitive user inputs.
