Method

Offline-Poly: A Polyhedral Framework For Offline 3D Multi-Object [Offline-Poly]
https://github.com/K544-AD/Offline-Poly

Submitted on 21 Feb. 2026 07:56 by
Offline-Poly Team (Harbin Institute of Technology)

Running time:0.01 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
We propose Offline-Poly, a robust and general
framework for offline 3D MOT built upon a novel
Tracking-By-Tracking paradigm.
Parameters:
TBD
Latex Bibtex:
@article{li2026offline,
title={Offline-Poly: A Polyhedral Framework For
Offline 3D Multi-Object Tracking},
author={Li, Xiaoyu and Wu, Yitao and Wu, Xian and
Zhuo, Haolin and Zhao, Lijun and Sun, Lining},
journal={arXiv preprint arXiv:2602.13772},
year={2026}
}

Detailed Results

From all 29 test sequences, our benchmark computes the commonly used tracking metrics CLEARMOT, MT/PT/ML, identity switches, and fragmentations [1,2]. The tables below show all of these metrics.


Benchmark MOTA MOTP MODA MODP
CAR 93.25 % 86.67 % 93.35 % 89.34 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
CAR 97.19 % 97.05 % 97.12 % 38566 1172 1114 10.54 % 46571 773

Benchmark MT PT ML IDS FRAG
CAR 91.69 % 6.15 % 2.15 % 36 77

This table as LaTeX

[1] K. Bernardin, R. Stiefelhagen: Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. JIVP 2008.
[2] Y. Li, C. Huang, R. Nevatia: Learning to associate: HybridBoosted multi-target tracker for crowded scene. CVPR 2009.


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