\begin{tabular}{c | c | c | c | c}
{\bf Method} & {\bf Moderate} & {\bf Easy} & {\bf Hard} & {\bf Runtime}\\ \hline
VMVS \cite{ku2018joint} & 68.19 \% & 79.98 \% & 63.18 \% & 0.25 s / GPU \\
SubCNN \cite{xiang2017subcategory} & 66.70 \% & 79.65 \% & 61.35 \% & 2 s / GPU \\
F-ConvNet \cite{wang2019frustum} & 63.87 \% & 75.19 \% & 58.57 \% & 0.47 s / GPU \\
3DOP \cite{Chen2015NIPS} & 61.48 \% & 74.22 \% & 55.89 \% & 3s / GPU \\
DeepStereoOP \cite{Pham2017SPIC} & 60.15 \% & 73.76 \% & 55.30 \% & 3.4 s / GPU \\
Pose-RCNN \cite{braun2016pose} & 59.84 \% & 76.24 \% & 53.59 \% & 2 s / >8 cores \\
Mono3D \cite{Chen2016CVPR} & 58.66 \% & 71.19 \% & 53.94 \% & 4.2 s / GPU \\
MonoPSR \cite{ku2019monopsr} & 54.65 \% & 68.98 \% & 50.07 \% & 0.2 s / GPU \\
FRCNN+Or \cite{GuindelITSM} & 52.15 \% & 67.03 \% & 47.14 \% & 0.09 s / \\
PointPillars \cite{lang2018pointpillars} & 48.05 \% & 57.47 \% & 45.40 \% & 16 ms / \\
MMLab-PointRCNN \cite{shi2019pointrcnn} & 47.33 \% & 57.19 \% & 44.31 \% & 0.1 s / GPU \\
Shift R-CNN (mono) \cite{shiftrcnn} & 46.56 \% & 64.73 \% & 41.86 \% & 0.25 s / GPU \\
VOXEL\_FPN\_HR \cite{ERROR: Wrong syntax in BIBTEX file.} & 45.65 \% & 56.17 \% & 42.10 \% & 0.12 s / 8 cores \\
AVOD-FPN \cite{ku2018joint} & 43.99 \% & 53.48 \% & 41.56 \% & 0.1 s / \\
AB3DMOT \cite{Weng2019} & 39.76 \% & 50.30 \% & 36.90 \% & 0.0047s / 1 core \\
SS3D \cite{DBLPjournalscorrabs190608070} & 39.60 \% & 53.72 \% & 35.40 \% & 48 ms / \\
SECOND \cite{yan2018second} & 39.53 \% & 50.18 \% & 36.25 \% & 38 ms / \\
DPM-VOC+VP \cite{Pepik2015PAMI} & 37.79 \% & 52.91 \% & 33.27 \% & 8 s / 1 core \\
SCNet \cite{8813061} & 35.49 \% & 44.50 \% & 33.38 \% & 0.04 s / GPU \\
IPOD \cite{yang2018ipod} & 34.31 \% & 42.37 \% & 31.61 \% & 0.2 s / GPU \\
sensekitti \cite{binyang16craft} & 34.26 \% & 41.03 \% & 31.51 \% & 4.5 s / GPU \\
LSVM-MDPM-sv \cite{Felzenszwalb2010PAMI} & 33.01 \% & 45.60 \% & 29.27 \% & 10 s / 4 cores \\
AVOD \cite{ku2018joint} & 32.19 \% & 42.54 \% & 29.09 \% & 0.08 s / \\
Complexer-YOLO \cite{Simon2019CVPRWorkshops} & 32.13 \% & 37.32 \% & 28.94 \% & 0.06 s / GPU \\
RPN+BF \cite{Zhang2016ECCV} & 32.12 \% & 41.19 \% & 28.83 \% & 0.6 s / GPU \\
M3D-RPN \cite{brazil2019m3drpn} & 31.88 \% & 44.33 \% & 28.55 \% & 0.16 s / GPU \\
ODES \cite{ERROR: Wrong syntax in BIBTEX file.} & 31.79 \% & 37.79 \% & 28.66 \% & 0.02 s / GPU \\
SubCat \cite{OhnBar2014CVPRWORK} & 31.26 \% & 42.31 \% & 27.39 \% & 1.2 s / 6 cores \\
ACF \cite{Dollar2014PAMI} & 24.31 \% & 32.23 \% & 21.70 \% & 1 s / 1 core \\
multi-task CNN \cite{Oeljeklaus18} & 22.80 \% & 30.30 \% & 20.47 \% & 25.1 ms / GPU \\
ACF-MR \cite{Nattoji2016TITS} & 22.61 \% & 29.23 \% & 20.08 \% & 0.6 s / 1 core \\
DPM-C8B1 \cite{Yebes2015SENSORS} & 19.17 \% & 27.79 \% & 16.48 \% & 15 s / 4 cores \\
BirdNet \cite{BirdNet2018} & 16.45 \% & 21.07 \% & 15.65 \% & 0.11 s / \\
RT3DStereo \cite{Koenigshof2019Objects} & 15.34 \% & 21.41 \% & 13.23 \% & 0.08 s / GPU
\end{tabular}