The KITTI Vision Benchmark Suite

We apply ReMOTS on public detections.
The confidence threshold of public detection are:
Pedestrian: 0.2
Car: 0.5

The process is:
(1) Training the appearance encoder using predicted
masks.
(2) Associating observations across adjacent frames
to form short-term tracklets.
(3) Training the appearance encoder using short-
term tracklets as reliable pseudo labels.
(4) Merging short-term tracklets to long-term
tracklets utilizing adopted appearance features and
thresholds that are automatically obtained from
statistical information.

For more details please refer to our paper.

N

@misc{yang2020remots,
title={ReMOTS: Self-Supervised Refining Multi-
Object Tracking and Segmentation},
author={Fan Yang and Xin Chang and Chenyu Dang
and Ziqiang Zheng and Sakriani Sakti and Satoshi
Nakamura and Yang Wu},
year={2020},
eprint={2007.03200},
archivePrefix={arXiv},
primaryClass={cs.CV}
}