  We present a method for recovering the shared content between two visual
domains as well as the content that is unique to each domain. This allows us to
map from one domain to the other, in a way in which the content that is
specific for the first domain is removed and the content that is specific for
the second is imported from any image in the second domain. In addition, our
method enables generation of images from the intersection of the two domains as
well as their union, despite having no such samples during training. The method
is shown analytically to contain all the sufficient and necessary constraints.
It also outperforms the literature methods in an extensive set of experiments.
Our code is available at
https://github.com/sagiebenaim/DomainIntersectionDifference.
