Method

AttriMOT [AttriMOT]
[Anonymous Submission]

Submitted on 23 Jan. 2026 06:56 by
[Anonymous Submission]

Running time:0.01 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
NA
Parameters:
NA
Latex Bibtex:
NA

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 80.05 % 77.85 % 83.00 % 84.01 % 84.12 % 86.59 % 90.04 % 87.53 %

Benchmark TP FP FN
CAR 32793 1599 1556

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 90.32 % 86.11 % 90.83 % 174 77.08 %

Benchmark MT rate PT rate ML rate FRAG
CAR 85.85 % 10.77 % 3.38 % 104

Benchmark # Dets # Tracks
CAR 34349 924

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.


eXTReMe Tracker