English

UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution

Computer Vision and Pattern Recognition 2021-11-03 v2

Abstract

In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method. The first step performs instance segmentation for each frame to get a large number of instance mask proposals. The second step is to do inter-frame instance mask matching with the help of optical flow. We demonstrate that with high quality mask proposals, a simple matching mechanism is good enough for tracking. Our approach achieves the first place in the UVO 2021 Video-based Open-World Segmentation Challenge.

Keywords

Cite

@article{arxiv.2110.11661,
  title  = {UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution},
  author = {Yuming Du and Wen Guo and Yang Xiao and Vincent Lepetit},
  journal= {arXiv preprint arXiv:2110.11661},
  year   = {2021}
}

Comments

Code:https://github.com/dulucas/UVO_Challenge. arXiv admin note: substantial text overlap with arXiv:2110.10239

R2 v1 2026-06-24T07:05:59.187Z