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3D Object Detection on KITTI (test)

87.87AP_3D (Easy)Patch Refinement
-1.143621.965745.07568.1843Nov 9, 2018Apr 3, 2019Aug 26, 2019Jan 18, 2020Jun 11, 2020Nov 3, 2020Mar 29, 2021

Evaluation results

MethodLinks
Patch RefinementModality=LiDAR2019.1087.8777.1668.91
MMFModality=RGB + LiDAR, custom train-val split=true2019.1086.8176.7568.41
UberATG-MMFModality=L+I, Time (ms)=802019.1186.8176.7568.41
MMFLiDAR=true, IMG=true, Time (ms)=802020.1286.8176.7568.41
STDModality=L, Time (ms)=802019.1186.6177.6376.06
PointRGCNModality=L, Time (ms)=2622019.1185.9775.7370.6
LiDAR R-CNNTraining Data Split=train+val2021.0385.9774.2169.18
PointRCNNModality=LiDAR2019.1085.9475.7668.32
PointRCNNModality=L, Time (ms)=1002019.1185.9475.7668.32
Fast Point R-CNNModality=L, Time (ms)=652019.1184.2875.7367.39
FPointNetInput=RGB+LIDAR2019.0483.7670.9263.65
RoarNet2018.1183.7173.0459.16
R-GCN onlyModality=L, Time (ms)=2392019.1183.4275.2668.73
MVX-Net (PF) (M)Modality=Multimodal, IoU threshold=0.7, Feature Fusion Technique=PointFusion2019.0483.272.765.2
SECONDModality=LiDAR2019.1083.1373.6666.2
SECONDModality=L, Time (ms)=502019.1183.1373.6666.2
SECONDLiDAR=true, IMG=false, Time (ms)=502020.1283.1373.6666.2
PointPillarsTraining Data Split=train+val2021.0383.1274.1169.14
UberATG-ContFuse2018.1182.5466.2264.04
ContFuseLiDAR=true, IMG=true, Time (ms)=602020.1282.5466.2264.04
Cont-Fuse (M)Modality=Multimodal, IoU threshold=0.72019.0482.566.264
PointPillarsTraining Data Split=train2021.0382.1772.8167.57
VoxelNetInput=RGB+LIDAR2019.0481.9765.4662.85
AVODarchitecture=FPN2018.1181.9471.8866.38
AVOD-FPNClass=Car2018.1281.9471.8866.38
AVOD-FPNModality=RGB + LiDAR, custom train-val split=true2019.1081.9471.8866.38
AVOD-FPNModality=L+I, Time (ms)=1002019.1181.9471.8866.38
AVOD-FPNLiDAR=true, IMG=true, Time (ms)=1002020.1281.9471.8866.38
AVOD-FPN (M)Modality=Multimodal, IoU threshold=0.72019.0481.971.966.4
F-PointNetversion=v22018.1181.270.3962.19
F-PointNetClass=Car2018.1281.270.3962.19
F-PointNet (M)Modality=Multimodal, IoU threshold=0.72019.0481.270.462.2
F-PointNetModality=RGB + LiDAR, custom train-val split=true2019.1081.270.3962.19
F-PointNetModality=L+I, Time (ms)=1702019.1181.270.3962.19
F-PointNetLiDAR=true, IMG=true, Time (ms)=1702020.1281.270.3962.19
IPODClass=Car2018.1279.7572.5766.33
PointPillarsModality=LiDAR, custom train-val split=true2019.1079.0574.9968.3
PointPillarsModality=L, Time (ms)=162019.1179.0574.9968.3
VoxelNet (S)Modality=Single, IoU threshold=0.72019.0477.565.157.7
VoxelNetModality=L, Time (ms)=2202019.1177.4965.1157.73
VoxelNetLiDAR=true, IMG=false, Time (ms)=2202020.1277.4965.1157.73
VoxelNet2018.1177.4765.1157.73
VoxelNetClass=Car2018.1277.4765.1157.73
VoxelnetModality=LiDAR2019.1077.4765.1157.73
AVOD (M)Modality=Multimodal, IoU threshold=0.72019.0473.665.858.4
AVODClass=Car2018.1273.5965.7858.38
AVODModality=L+I, Time (ms)=1002019.1173.5965.7858.38
AVODLiDAR=true, IMG=true, Time (ms)=802020.1273.5965.7858.38
F-PointNetClass=Cyclist2018.1271.9656.7750.39
IPODClass=Cyclist2018.1271.453.4648.34
MV3D (M)Modality=Multimodal, IoU threshold=0.72019.0471.162.455.1
MV3D2018.1171.0962.3555.12
MV3DClass=Car2018.1271.0962.3555.12
MV3DModality=RGB + LiDAR2019.1071.0962.3555.12
MV3DLiDAR=true, IMG=true, Time (ms)=3602020.1271.0962.3555.12
MV3D (S)Modality=Single, IoU threshold=0.72019.0466.852.751.3
MV3DModality=L+I, Time (ms)=2402019.1166.7752.7351.31
MV3DLiDAR=true, IMG=false, Time (ms)=2402020.1266.7752.7351.31
AVOD-FPNClass=Cyclist2018.126452.1846.61
VoxelNetClass=Cyclist2018.1261.2248.3644.37
AVODClass=Cyclist2018.1260.1144.938.8
IPODClass=Pedestrian2018.1256.9244.6842.39
PL-AVOD2019.0955.437.1731.37
OC Stereo2019.0955.1138.831.86
F-PointNetClass=Pedestrian2018.1251.2144.8940.23
AVOD-FPNClass=Pedestrian2018.1250.842.8140.88
Stereo R-CNNIoU threshold=0.72019.0249.2334.0528.39
S-RCNN2019.0949.2334.0528.39
PL-FP2019.0939.726.722.3
VoxelNetClass=Pedestrian2018.1239.4833.6931.51
AVODClass=Pedestrian2018.1238.2831.5126.98
M3D-RPNtime=0.16s2020.0114.769.717.42
MonoGRNetInput=RGB2019.0413.8810.197.62
RTM3Dbackbone=DLA-34, time=0.055s2020.0113.6110.098.18
MF3DInput=RGB2019.0410.535.695.39
MonoGRNettime=0.06s2020.019.615.744.25
GS3D2019.037.696.296.16
GS3Dtime=2.3s2020.017.696.296.16
MF3D2019.037.085.184.68
FQNettime=3.33s2020.012.771.511.01
Mono3DInput=RGB2019.042.532.312.31
OFT-NetModality=Mono2018.112.53.282.27
3D-SSMFCNNModality=Mono2018.112.282.391.52