  In this paper, we propose PolyTransform, a novel instance segmentation
algorithm that produces precise, geometry-preserving masks by combining the
strengths of prevailing segmentation approaches and modern polygon-based
methods. In particular, we first exploit a segmentation network to generate
instance masks. We then convert the masks into a set of polygons that are then
fed to a deforming network that transforms the polygons such that they better
fit the object boundaries. Our experiments on the challenging Cityscapes
dataset show that our PolyTransform significantly improves the performance of
the backbone instance segmentation network and ranks 1st on the Cityscapes
test-set leaderboard. We also show impressive gains in the interactive
annotation setting. We release the code at
https://github.com/uber-research/PolyTransform.
