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.

本文介绍了2017年DAVIS视频物体分割挑战赛，该挑战赛是一个公共数据集，评测方法和比赛，它是为了特别针对视频物体分割任务而设计的，挑战赛遵循其他成功首创的做法，如ILSVRC和PASCAL VOC，DAVIS挑战赛包括数据集、评估方法和与CVPR 2017同地举办的独立工作坊，本文还描述了该基准测试的范围、数据集的主要特征、竞赛的评价指标，并对参赛者的结果进行了详细分析。

2017年DAVIS视频对象分割挑战赛