\begin{tabular}{c | c | c | c | c | c | c | c | c | c | c}
{\bf Method} & {\bf PRE-20} & {\bf F1-20} & {\bf HR-20} & {\bf PRE-30} & {\bf F1-30} & {\bf HR-30} & {\bf PRE-40} & {\bf F1-40} & {\bf HR-40} & {\bf Runtime}\\ \hline
CyberMELD \cite{9110871} & 99.17 \% & 99.23 \% & 99.11 \% & 98.64 \% & 98.00 \% & 97.55 \% & 94.57 \% & 89.66 \% & 90.79 \% & 0.05 s / 8 core \\
CyberMELD+PLARD \cite{9110871} & 99.18 \% & 99.36 \% & 99.29 \% & 98.70 \% & 98.20 \% & 97.17 \% & 96.74 \% & 90.80 \% & 90.79 \% & 0.18 s / 8 cores \\
RBNet \cite{chen2017rbnet} & 99.24 \% & 99.33 \% & 99.21 \% & 98.74 \% & 97.34 \% & 95.92 \% & 95.56 \% & 87.21 \% & 81.58 \% & 0.18 s / GPU \\
RoadNet3 \cite{lyu2019road} & 99.18 \% & 99.21 \% & 99.07 \% & 98.39 \% & 97.23 \% & 95.57 \% & 94.57 \% & 83.72 \% & 80.26 \% & 300 ms / GPU \\
Up-Conv-Poly \cite{Oliveira2016IROS} & 99.06 \% & 98.84 \% & 98.45 \% & 97.57 \% & 95.27 \% & 93.14 \% & 90.11 \% & 83.72 \% & 77.63 \% & 0.08 s / GPU \\
SPRAY \cite{Kuehnl2012ITSC} & 97.58 \% & 96.74 \% & 96.38 \% & 96.59 \% & 94.16 \% & 92.06 \% & 87.64 \% & 78.57 \% & 62.16 \% & 45 ms / \\
SPlane + BL \cite{Einecke2014IV} & 95.53 \% & 92.88 \% & 91.21 \% & 91.89 \% & 87.12 \% & 74.28 \% & 79.79 \% & 47.13 \% & 0.00 \% & 2 s / 1 core \\
SCRFFPFHGSP \cite{Gheorghe2015} & 94.88 \% & 87.95 \% & 82.98 \% & 87.91 \% & 78.90 \% & 71.95 \% & 60.64 \% & 43.68 \% & 38.16 \% & 5 s / 8 cores
\end{tabular}