  Image compositing is a key step in film making and image editing that aims to
segment a foreground object and combine it with a new background. Automatic
image compositing can be done easily in a studio using chroma-keying when the
background is pure blue or green. However, image compositing in natural scenes
with complex backgrounds remains a tedious task, requiring experienced artists
to hand-segment. In order to achieve automatic compositing in natural scenes,
we propose a fully automated method that integrates instance segmentation and
image matting processes to generate high-quality semantic mattes that can be
used for image editing task. Our approach can be seen both as a refinement of
existing instance segmentation algorithms and as a fully automated semantic
image matting method. It extends automatic image compositing techniques such as
chroma-keying to scenes with complex natural backgrounds without the need for
any kind of user interaction. The output of our approach can be considered as
both refined instance segmentations and alpha mattes with semantic meanings. We
provide experimental results which show improved performance results as
compared to existing approaches.
