\begin{tabular}{c | c | c | c | c}
{\bf Method} & {\bf Moderate} & {\bf Easy} & {\bf Hard} & {\bf Runtime}\\ \hline
MMLab-PartA^2 \cite{shi2019part} & 76.74 \% & 85.37 \% & 69.63 \% & 0.08 s / GPU \\
F-ConvNet \cite{wang2019frustum} & 74.96 \% & 84.38 \% & 66.45 \% & 0.47 s / GPU \\
MMLab-PointRCNN \cite{shi2019pointrcnn} & 72.35 \% & 83.40 \% & 65.50 \% & 0.1 s / GPU \\
AB3DMOT \cite{Weng2019} & 68.91 \% & 80.68 \% & 62.30 \% & 0.0047s / 1 core \\
PointPillars \cite{lang2018pointpillars} & 68.16 \% & 82.43 \% & 61.96 \% & 16 ms / \\
SubCNN \cite{xiang2017subcategory} & 63.41 \% & 71.39 \% & 56.34 \% & 2 s / GPU \\
Pose-RCNN \cite{braun2016pose} & 62.25 \% & 74.85 \% & 55.09 \% & 2 s / >8 cores \\
SCNet \cite{8813061} & 60.32 \% & 76.87 \% & 56.16 \% & 0.04 s / GPU \\
Deep3DBox \cite{MousavianCVPR2017} & 59.37 \% & 68.58 \% & 51.97 \% & 1.5 s / GPU \\
3DOP \cite{Chen2015NIPS} & 58.59 \% & 71.95 \% & 52.35 \% & 3s / GPU \\
AVOD-FPN \cite{ku2018joint} & 57.53 \% & 67.61 \% & 54.16 \% & 0.1 s / \\
SECOND \cite{yan2018second} & 57.20 \% & 80.97 \% & 55.14 \% & 38 ms / \\
Complexer-YOLO \cite{Simon2019CVPRWorkshops} & 56.32 \% & 64.51 \% & 56.23 \% & 0.06 s / GPU \\
DeepStereoOP \cite{Pham2017SPIC} & 55.62 \% & 67.49 \% & 48.85 \% & 3.4 s / GPU \\
AVOD \cite{ku2018joint} & 54.43 \% & 64.36 \% & 47.67 \% & 0.08 s / \\
Mono3D \cite{Chen2016CVPR} & 53.11 \% & 65.74 \% & 48.87 \% & 4.2 s / GPU \\
FRCNN+Or \cite{GuindelITSM} & 50.91 \% & 63.41 \% & 45.46 \% & 0.09 s / \\
MonoPSR \cite{ku2019monopsr} & 49.30 \% & 58.93 \% & 43.45 \% & 0.2 s / GPU \\
sensekitti \cite{binyang16craft} & 42.12 \% & 46.65 \% & 36.66 \% & 4.5 s / GPU \\
Shift R-CNN (mono) \cite{shiftrcnn} & 34.77 \% & 54.31 \% & 34.04 \% & 0.25 s / GPU \\
ODES \cite{ERROR: Wrong syntax in BIBTEX file.} & 33.74 \% & 37.75 \% & 30.34 \% & 0.02 s / GPU \\
M3D-RPN \cite{brazil2019m3drpn} & 33.07 \% & 51.41 \% & 31.46 \% & 0.16 s / GPU \\
SS3D \cite{DBLPjournalscorrabs190608070} & 31.17 \% & 44.77 \% & 28.96 \% & 48 ms / \\
BirdNet \cite{BirdNet2018} & 30.76 \% & 41.48 \% & 28.66 \% & 0.11 s / \\
DPM-VOC+VP \cite{Pepik2015PAMI} & 23.22 \% & 31.24 \% & 21.62 \% & 8 s / 1 core \\
LSVM-MDPM-sv \cite{Felzenszwalb2010PAMI} & 23.14 \% & 28.89 \% & 22.28 \% & 10 s / 4 cores \\
DPM-C8B1 \cite{Yebes2015SENSORS} & 19.25 \% & 27.16 \% & 17.95 \% & 15 s / 4 cores \\
RT3DStereo \cite{Koenigshof2019Objects} & 5.26 \% & 6.60 \% & 3.68 \% & 0.08 s / GPU
\end{tabular}