The 2018 DAVIS Challenge on Video Object Segmentation
This work provides a benchmark for researchers in video object segmentation, but it is incremental as it extends an existing dataset and competition framework.
The paper introduces the 2018 DAVIS Challenge, a competition for video object segmentation that builds on the DAVIS 2017 dataset by adding 100 videos with multiple objects and includes a new interactive segmentation teaser track.
We present the 2018 DAVIS Challenge on Video Object Segmentation, a public competition specifically designed for the task of video object segmentation. It builds upon the DAVIS 2017 dataset, which was presented in the previous edition of the DAVIS Challenge, and added 100 videos with multiple objects per sequence to the original DAVIS 2016 dataset. Motivated by the analysis of the results of the 2017 edition, the main track of the competition will be the same than in the previous edition (segmentation given the full mask of the objects in the first frame -- semi-supervised scenario). This edition, however, also adds an interactive segmentation teaser track, where the participants will interact with a web service simulating the input of a human that provides scribbles to iteratively improve the result.