Method

Anonymous [Anonymous]
[Anonymous Submission]

Submitted on 23 Mar. 2026 11:20 by
[Anonymous Submission]

Running time:1e-4 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Anonymous
Parameters:
Anonymous
Latex Bibtex:
Anonymous

Detailed Results

From all 29 test sequences, our benchmark computes the HOTA tracking metrics (HOTA, DetA, AssA, DetRe, DetPr, AssRe, AssPr, LocA) [1] as well as the CLEARMOT, MT/PT/ML, identity switches, and fragmentation [2,3] metrics. The tables below show all of these metrics.


Benchmark HOTA DetA AssA DetRe DetPr AssRe AssPr LocA
CAR 83.10 % 79.95 % 87.10 % 85.41 % 85.38 % 89.81 % 91.76 % 87.94 %

Benchmark TP FP FN
CAR 33113 1279 1289

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 92.40 % 86.68 % 92.53 % 46 79.57 %

Benchmark MT rate PT rate ML rate FRAG
CAR 88.77 % 9.08 % 2.15 % 74

Benchmark # Dets # Tracks
CAR 34402 740

This table as LaTeX


This figure as: png pdf

[1] J. Luiten, A. Os̆ep, P. Dendorfer, P. Torr, A. Geiger, L. Leal-Taixé, B. Leibe: HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. IJCV 2020.
[2] K. Bernardin, R. Stiefelhagen: Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. JIVP 2008.
[3] Y. Li, C. Huang, R. Nevatia: Learning to associate: HybridBoosted multi-target tracker for crowded scene. CVPR 2009.


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