\begin{tabular}{c | c | c | c | c | c | c | c | c | c}
{\bf Method} & {\bf HOTA} & {\bf DetA} & {\bf AssA} & {\bf DetRe} & {\bf DetPr} & {\bf AssRe} & {\bf AssPr} & {\bf LocA} & {\bf MOTA}\\ \hline
OC-SORT \cite{cao2022observationcentric} & 54.69 \% & 50.82 \% & 59.08 \% & 55.68 \% & 70.94 \% & 64.09 \% & 73.36 \% & 78.52 \% & 65.14 \%\\
RAM \cite{tokmakov2022object} & 52.71 \% & 53.55 \% & 52.19 \% & 58.86 \% & 70.17 \% & 59.49 \% & 64.99 \% & 77.70 \% & 68.40 \%\\
SRK\_ODESA(hp) \cite{ODESA2020} & 50.87 \% & 53.43 \% & 48.78 \% & 57.79 \% & 72.90 \% & 53.45 \% & 71.33 \% & 78.81 \% & 68.04 \%\\
CgOSNet \cite{ERROR: Wrong syntax in BIBTEX file.} & 50.08 \% & 46.26 \% & 54.81 \% & 49.45 \% & 68.60 \% & 60.34 \% & 70.54 \% & 75.36 \% & 60.78 \%\\
PermaTrack \cite{tokmakov2021learning} & 48.63 \% & 52.28 \% & 45.61 \% & 57.40 \% & 71.03 \% & 49.63 \% & 73.28 \% & 78.57 \% & 65.98 \%\\
Opm-NC2 \cite{2022IEEE sensors journal} & 46.55 \% & 46.82 \% & 46.68 \% & 53.01 \% & 59.38 \% & 50.84 \% & 65.82 \% & 72.07 \% & 56.05 \%\\
3D-TLSR \cite{nguyen20203d} & 46.34 \% & 42.03 \% & 51.32 \% & 44.51 \% & 71.14 \% & 54.45 \% & 73.11 \% & 76.87 \% & 53.58 \%\\
TuSimple \cite{choi2015near} & 45.88 \% & 44.66 \% & 47.62 \% & 47.92 \% & 69.51 \% & 52.04 \% & 69.88 \% & 76.43 \% & 57.61 \%\\
CAT \cite{isprsannalsIV2W5532019} & 45.65 \% & 42.43 \% & 49.55 \% & 45.89 \% & 67.79 \% & 53.20 \% & 71.97 \% & 75.90 \% & 51.96 \%\\
MPNTrack \cite{braso2020CVPR} & 45.26 \% & 43.74 \% & 47.28 \% & 53.62 \% & 58.30 \% & 52.18 \% & 68.47 \% & 75.93 \% & 46.23 \%\\
NC2 \cite{2021arXiv} & 44.30 \% & 42.31 \% & 46.75 \% & 52.97 \% & 52.43 \% & 50.91 \% & 65.83 \% & 72.08 \% & 44.18 \%\\
SRK\_ODESA(mp) \cite{ODESA2020} & 43.73 \% & 53.73 \% & 36.05 \% & 58.01 \% & 73.19 \% & 40.05 \% & 69.44 \% & 78.91 \% & 67.31 \%\\
Be-Track \cite{s19020391} & 43.36 \% & 39.99 \% & 47.23 \% & 43.00 \% & 69.03 \% & 51.28 \% & 69.60 \% & 76.78 \% & 50.85 \%\\
Mono\_3D\_KF \cite{9626850} & 42.87 \% & 40.13 \% & 46.31 \% & 46.02 \% & 59.91 \% & 52.86 \% & 63.50 \% & 74.03 \% & 45.44 \%\\
TripletTrack \cite{Marinello2022CVPR} & 42.77 \% & 39.54 \% & 46.54 \% & 41.97 \% & 71.91 \% & 50.86 \% & 71.26 \% & 77.93 \% & 50.08 \%\\
MDP \cite{Xiang2015ICCV} & 42.76 \% & 39.23 \% & 47.13 \% & 43.83 \% & 63.02 \% & 50.91 \% & 71.04 \% & 75.15 \% & 47.02 \%\\
Quasi-Dense \cite{pang2021quasidense} & 41.12 \% & 44.81 \% & 38.10 \% & 48.55 \% & 70.39 \% & 41.02 \% & 72.47 \% & 77.87 \% & 55.55 \%\\
QD-3DT \cite{Hu2021QD3DT} & 41.08 \% & 44.01 \% & 38.82 \% & 48.96 \% & 67.19 \% & 42.09 \% & 72.44 \% & 77.38 \% & 51.77 \%\\
NOMT* \cite{Choi2015ICCV} & 40.91 \% & 37.52 \% & 44.79 \% & 40.94 \% & 65.86 \% & 50.53 \% & 65.94 \% & 75.94 \% & 47.08 \%\\
CenterTrack \cite{zhou2020tracking} & 40.35 \% & 44.48 \% & 36.93 \% & 49.91 \% & 66.83 \% & 41.05 \% & 70.19 \% & 77.81 \% & 53.84 \%\\
RMOT* \cite{Yoon2015WACV} & 39.56 \% & 36.07 \% & 43.63 \% & 39.74 \% & 63.97 \% & 49.54 \% & 62.82 \% & 75.35 \% & 43.32 \%\\
JCSTD \cite{Tian2019MOT} & 39.44 \% & 34.20 \% & 45.79 \% & 36.15 \% & 69.39 \% & 49.38 \% & 69.00 \% & 76.23 \% & 43.42 \%\\
TrackMPNN \cite{rangesh2101trackmpnn} & 39.40 \% & 44.24 \% & 35.45 \% & 50.78 \% & 64.58 \% & 38.98 \% & 69.80 \% & 77.56 \% & 52.10 \%\\
EagerMOT \cite{Kim21ICRA} & 39.38 \% & 40.60 \% & 38.72 \% & 43.43 \% & 61.49 \% & 40.98 \% & 68.33 \% & 71.25 \% & 49.82 \%\\
AB3DMOT+PointRCNN \cite{Weng2020AB3DMOT} & 37.81 \% & 32.37 \% & 44.33 \% & 34.91 \% & 59.35 \% & 48.44 \% & 62.83 \% & 71.31 \% & 38.13 \%\\
NOMT \cite{Choi2015ICCV} & 36.26 \% & 31.87 \% & 41.63 \% & 34.61 \% & 61.26 \% & 46.88 \% & 62.25 \% & 72.83 \% & 36.52 \%\\
NOMT-HM* \cite{Choi2015ICCV} & 34.76 \% & 33.96 \% & 35.81 \% & 37.64 \% & 62.76 \% & 39.23 \% & 66.66 \% & 75.36 \% & 38.60 \%\\
SCEA* \cite{Yoon2016CVPR} & 34.66 \% & 34.31 \% & 35.21 \% & 36.70 \% & 67.74 \% & 38.33 \% & 69.46 \% & 76.23 \% & 43.26 \%\\
JRMOT \cite{Shenoi2020JRMOTAR} & 34.24 \% & 38.79 \% & 30.55 \% & 42.51 \% & 66.64 \% & 32.69 \% & 70.12 \% & 76.64 \% & 45.31 \%\\
RMOT \cite{Yoon2015WACV} & 34.09 \% & 29.61 \% & 39.45 \% & 32.12 \% & 60.92 \% & 43.14 \% & 63.59 \% & 72.99 \% & 34.05 \%\\
CIWT* \cite{Osep17ICRA} & 33.93 \% & 34.00 \% & 34.07 \% & 36.35 \% & 67.44 \% & 36.34 \% & 70.76 \% & 75.96 \% & 42.10 \%\\
LP-SSVM* \cite{Wang2016IJCV} & 33.74 \% & 35.74 \% & 32.03 \% & 39.54 \% & 63.11 \% & 36.36 \% & 63.24 \% & 75.18 \% & 43.42 \%\\
MCMOT-CPD \cite{Lee2016ECCVWORK} & 32.06 \% & 36.30 \% & 28.83 \% & 39.06 \% & 68.00 \% & 32.14 \% & 69.60 \% & 76.67 \% & 44.19 \%\\
NOMT-HM \cite{Choi2015ICCV} & 31.13 \% & 25.64 \% & 38.23 \% & 27.75 \% & 59.78 \% & 42.38 \% & 65.06 \% & 72.90 \% & 26.86 \%\\
LP-SSVM \cite{Wang2016IJCV} & 28.19 \% & 29.29 \% & 27.57 \% & 31.61 \% & 60.77 \% & 31.12 \% & 61.78 \% & 72.49 \% & 32.42 \%\\
SCEA \cite{Yoon2016CVPR} & 27.80 \% & 27.41 \% & 28.61 \% & 29.38 \% & 62.30 \% & 30.44 \% & 68.62 \% & 73.55 \% & 31.75 \%\\
CEM \cite{Milan2014PAMI} & 25.83 \% & 25.54 \% & 26.41 \% & 27.54 \% & 60.66 \% & 27.91 \% & 68.34 \% & 73.43 \% & 26.59 \%\\
Complexer-YOLO \cite{Simon2019CVPRWorkshops} & 14.08 \% & 24.91 \% & 8.15 \% & 27.21 \% & 52.62 \% & 8.63 \% & 59.39 \% & 68.64 \% & 11.99 \%
\end{tabular}