Method

a tracking algorithm of sia [on] [siain]


Submitted on 24 Sep. 2021 06:43 by
Kwangjin Yoon (SI Analytics)

Running time:0.3 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
This is a tracking algorithm for the STEP dataset.
Our method can segment every pixel in an image and
track multiple objects at the same time.
To do so, we combine SOTA panoptic segmentation
algorithm with the transformer-based tracker.
Parameters:
more than 1M parameters
Latex Bibtex:
@misc{ryu2021endtoend,
title={An End-to-End Trainable Video Panoptic
Segmentation Method usingTransformers},
author={Jeongwon Ryu and Kwangjin Yoon},
year={2021},
eprint={2110.04009},
archivePrefix={arXiv},
primaryClass={cs.CV}
}

Detailed Results

From all 29 test sequences, our benchmark computes the STQ segmentation and tracking metric (STQ, AQ, SQ (IoU)). The tables below show all of these metrics.


Benchmark STQ AQ SQ (IoU)
KITTI-STEP 57.87 % 55.16 % 60.71 %

This table as LaTeX



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