\begin{tabular}{c | c | c | c | c}
{\bf Method} & {\bf Moderate} & {\bf Easy} & {\bf Hard} & {\bf Runtime}\\ \hline
TANet \cite{liu2019tanet} & 51.38 \% & 60.85 \% & 47.54 \% & 0.035s / GPU \\
MMLab PV-RCNN \cite{shi2020pv} & 50.57 \% & 59.86 \% & 46.74 \% & 0.08 s / 1 core \\
HotSpotNet \cite{chen2020object} & 50.53 \% & 57.39 \% & 46.65 \% & 0.04 s / 1 core \\
VMVS \cite{ku2018joint} & 50.34 \% & 60.34 \% & 46.45 \% & 0.25 s / GPU \\
AVOD-FPN \cite{ku2018joint} & 50.32 \% & 58.49 \% & 46.98 \% & 0.1 s / \\
3DSSD \cite{yang3DSSD20} & 49.94 \% & 60.54 \% & 45.73 \% & 0.04 s / GPU \\
PointPainting \cite{vora2019pointpainting} & 49.93 \% & 58.70 \% & 46.29 \% & 0.4 s / GPU \\
SemanticVoxels \cite{fei2020semanticvoxels} & 49.93 \% & 58.91 \% & 47.31 \% & 0.04 s / GPU \\
MMLab-PartA^2 \cite{shi2020part} & 49.81 \% & 59.04 \% & 45.92 \% & 0.08 s / GPU \\
F-PointNet \cite{qi2017frustum} & 49.57 \% & 57.13 \% & 45.48 \% & 0.17 s / GPU \\
F-ConvNet \cite{wang2019frustum} & 48.96 \% & 57.04 \% & 44.33 \% & 0.47 s / GPU \\
HVNet \cite{ye2020hvnet} & 48.86 \% & 54.84 \% & 46.33 \% & 0.03 s / GPU \\
STD \cite{std2019yang} & 48.72 \% & 60.02 \% & 44.55 \% & 0.08 s / GPU \\
PointPillars \cite{lang2018pointpillars} & 48.64 \% & 57.60 \% & 45.78 \% & 16 ms / \\
Point-GNN \cite{shi2020pointgnn} & 47.07 \% & 55.36 \% & 44.61 \% & 0.6 s / GPU \\
SCNet \cite{8813061} & 46.73 \% & 56.87 \% & 42.74 \% & 0.04 s / GPU \\
MMLab-PointRCNN \cite{shi2019pointrcnn} & 46.13 \% & 54.77 \% & 42.84 \% & 0.1 s / GPU \\
ARPNET \cite{Ye2019} & 45.92 \% & 55.48 \% & 42.54 \% & 0.08 s / GPU \\
Deformable PV-RCNN \cite{bhattacharyya2020deformable} & 45.82 \% & 52.03 \% & 43.81 \% & 0.08 s / 1 core \\
epBRM \cite{arxiv} & 45.49 \% & 52.48 \% & 42.75 \% & 0.10 s / 1 core \\
MLOD \cite{deng2019mlod} & 45.40 \% & 55.09 \% & 41.42 \% & 0.12 s / GPU \\
3DBN\_2 \cite{ERROR: Wrong syntax in BIBTEX file.} & 42.97 \% & 50.99 \% & 40.49 \% & 0.12 s / 1 core \\
VOXEL\_FPN\_HR \cite{ERROR: Wrong syntax in BIBTEX file.} & 41.62 \% & 50.18 \% & 38.30 \% & 0.12 s / 8 cores \\
AB3DMOT \cite{Weng2019} & 38.79 \% & 47.51 \% & 35.85 \% & 0.0047s / 1 core \\
BirdNet+ \cite{Barrera2020} & 38.28 \% & 45.53 \% & 35.37 \% & 0.1 s / \\
CSW3D \cite{hu2019csw3d} & 37.96 \% & 49.27 \% & 33.83 \% & 0.03 s / 4 cores \\
SparsePool \cite{wang2017fusing} & 34.15 \% & 43.33 \% & 31.78 \% & 0.13 s / 8 cores \\
AVOD \cite{ku2018joint} & 33.57 \% & 42.58 \% & 30.14 \% & 0.08 s / \\
SparsePool \cite{wang2017fusing} & 33.22 \% & 41.55 \% & 29.66 \% & 0.13 s / 8 cores \\
SF \cite{ERROR: Wrong syntax in BIBTEX file.} & 29.77 \% & 37.16 \% & 26.61 \% & 0.5 s / 1 core \\
CG-Stereo \cite{li2020confidence} & 29.56 \% & 39.24 \% & 25.87 \% & 0.57 s / \\
Disp R-CNN \cite{sun2020disprcnn} & 25.36 \% & 36.06 \% & 21.62 \% & 0.42 s / GPU \\
Disp R-CNN (velo) \cite{sun2020disprcnn} & 24.95 \% & 35.39 \% & 21.30 \% & 0.42 s / GPU \\
BirdNet \cite{BirdNet2018} & 23.06 \% & 28.20 \% & 21.65 \% & 0.11 s / \\
OC Stereo \cite{pon2020object} & 20.80 \% & 29.79 \% & 18.62 \% & 0.35 s / 1 core \\
DSGN \cite{Chen2020dsgn} & 20.75 \% & 26.61 \% & 18.86 \% & 0.67 s / \\
Complexer-YOLO \cite{Simon2019CVPRWorkshops} & 18.26 \% & 21.42 \% & 17.06 \% & 0.06 s / GPU \\
TopNet-Retina \cite{8569433} & 14.57 \% & 18.04 \% & 12.48 \% & 52ms / \\
TopNet-HighRes \cite{8569433} & 13.50 \% & 19.43 \% & 11.93 \% & 101ms / \\
RefinedMPL \cite{vianney2019refinedmpl} & 7.92 \% & 13.09 \% & 7.25 \% & 0.15 s / GPU \\
MonoPair \cite{chen2020cvpr} & 7.04 \% & 10.99 \% & 6.29 \% & 0.06 s / GPU \\
TopNet-DecayRate \cite{8569433} & 6.59 \% & 8.78 \% & 6.25 \% & 92 ms / \\
Shift R-CNN (mono) \cite{shiftrcnn} & 5.66 \% & 8.58 \% & 4.49 \% & 0.25 s / GPU \\
TopNet-UncEst \cite{wirges2019capturing} & 4.60 \% & 6.88 \% & 3.79 \% & 0.09 s / \\
MonoPSR \cite{ku2019monopsr} & 4.56 \% & 7.24 \% & 4.11 \% & 0.2 s / GPU \\
M3D-RPN \cite{brazil2019m3drpn} & 4.05 \% & 5.65 \% & 3.29 \% & 0.16 s / GPU \\
D4LCN \cite{ding2019learning} & 3.86 \% & 5.06 \% & 3.59 \% & 0.2 s / GPU \\
RT3DStereo \cite{Koenigshof2019Objects} & 3.65 \% & 4.72 \% & 3.00 \% & 0.08 s / GPU \\
SS3D \cite{DBLPjournalscorrabs190608070} & 2.09 \% & 2.48 \% & 1.61 \% & 48 ms / \\
mBoW \cite{Behley2013IROS} & 0.00 \% & 0.00 \% & 0.00 \% & 10 s / 1 core
\end{tabular}