DAVIS Challenge on Video Object Segmentation 2018

Workshop in conjunction with CVPR 2018, Salt Lake City, Utah

Interactive Video Object Segmentation?

The semi-supervised case assumes the user inputs a full mask of the object of interest. We believe that it makes sense to explore the interactive scenario, where the user gives iterative refinement inputs to the algorithm.

How are you going to evaluate that?

The main idea is that our servers will simulate human interaction in the form of scribbles. A participant will connect to our servers and receive a set of scribbles, to which they should reply with a video segmentation. The servers will register the time spent and the quality of the results, and then reply with a refinement scribble. The curve of quality versus speed will serve as the evaluation criterion. You can find detailed information on the paper below.


The submissions will open end of March.

Why teaser?

The technical challenges behind this track make us be cautious about this first edition, so we launch in beta mode. We will make our best to make it work, but we cannot guarantee it 100%.

So why participate?

Despite not being a full-fledged competition, if results are interesting, we will treat them with the same honors as those in the main challenge (presentation, associated paper, etc.) and you get to be the among the first participants in the track.



The 2018 DAVIS Challenge on Video Object Segmentation
J. Pont-Tuset, S. Caelles, F. Perazzi, A. Montes, K.-K. Maninis, Y. Chen, and L. Van Gool
arXiv:1803.00557, 2018
[PDF] [BibTex]

  author = {Jordi Pont-Tuset and Sergi Caelles and Federico Perazzi and Alberto Montes and Kevis-Kokitsi Maninis and Yuhua Chen and Luc {Van Gool}},
  title = {The 2018 DAVIS Challenge on Video Object Segmentation},
  journal = {arXiv:1803.00557},
  year = {2018}

A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung
Computer Vision and Pattern Recognition (CVPR) 2016
[PDF] [Supplemental] [BibTex]

author = {F. Perazzi and J. Pont-Tuset and B. McWilliams and L. {Van Gool} and M. Gross and A. Sorkine-Hornung},
title = {A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation},
booktitle = {Computer Vision and Pattern Recognition},
year = {2016}
Please cite both papers in your publications if DAVIS helps your research.