  We present the 2019 DAVIS Challenge on Video Object Segmentation, the third
edition of the DAVIS Challenge series, a public competition designed for the
task of Video Object Segmentation (VOS). In addition to the original
semi-supervised track and the interactive track introduced in the previous
edition, a new unsupervised multi-object track will be featured this year. In
the newly introduced track, participants are asked to provide non-overlapping
object proposals on each image, along with an identifier linking them between
frames (i.e. video object proposals), without any test-time human supervision
(no scribbles or masks provided on the test video). In order to do so, we have
re-annotated the train and val sets of DAVIS 2017 in a concise way that
facilitates the unsupervised track, and created new test-dev and test-challenge
sets for the competition. Definitions, rules, and evaluation metrics for the
unsupervised track are described in detail in this paper.
