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arXiv · 1905.00737

The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation

Sergi Caelles·Jordi Pont-Tuset·Federico Perazzi·Alberto Montes·Kevis-Kokitsi Maninis·Luc Van Gool
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Abstract

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.

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Sergi Caelles, Jordi Pont-Tuset, Federico Perazzi, Alberto Montes, Kevis-Kokitsi Maninis, Luc Van Gool. 2019-05-02. The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation. https://arxiv.org/abs/1905.00737

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