We present the 2017 DAVIS Challenge, a public competition specifically designed for the task of video object segmentation. Following the footsteps of other successful initiatives, such as ILSVRC and PASCAL VOC, which established the avenue of research in the fields of scene classification and semantic segmentation, the DAVIS Challenge comprises a dataset, an evaluation methodology, and a public competition with a dedicated workshop co-located with CVPR 2017. The DAVIS Challenge follows up on the recent publication of DAVIS (Densely-Annotated VIdeo Segmentation), which has fostered the development of several novel state-of-the-art video object segmentation techniques. In this paper we describe the scope of the benchmark, highlight the main characteristics of the dataset and define the evaluation metrics of the competition. References: https://arxiv.org/abs/1704.00675 http://davischallenge.org/challenge2017/index.htmlA Benchmark Dataset and Evaluation Methodology for Video Object Segmentation.