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Monocular 3D Object Detection on KITTI (val)

17.06AP_R11 (Moderate)M3D-RPN
2.71846.441710.16513.8883Jun 7, 2020

Evaluation results

MethodLinks
M3D-RPNClass=Car2020.0617.0620.2715.21—————————
CubifAE-3DClass=Cyclist, Backbone=vgg-162020.0612.1812.9312.09—————————
M3D-RPNClass=Pedestrian2020.0611.28———————————
CubifAE-3DClass=Car, Backbone=vgg-162020.0611.29.8912.33—————————
GS3DClass=Car2020.0610.5111.6310.51—————————
MonoGRNetClass=Car2020.0610.1913.887.62—————————
M3D-RPNClass=Cyclist2020.0610.01———————————
CubifAE-3DClass=Car2020.069.217.9410.43—————————
CubifAE-3DClass=Cyclist2020.068.618.279.01—————————
Mono3D++Class=Car2020.067.910.65.7—————————
Barabanau et al.Class=Car2020.067.3713.964.54—————————
CubifAE-3DClass=Pedestrian, Backbone=vgg-162020.066.826.747.04—————————
ROI-10DClass=Car2020.066.639.616.29—————————
MF3DClass=Car2020.065.6910.535.39—————————
FQNetClass=Car2020.065.55.984.75—————————
CubifAE-3DClass=Pedestrian2020.064.794.644.96—————————
OFT-NetClass=Car2020.063.274.073.29—————————
Calibrated TeacherBackbone=ResNet-502026.04———17.1412.9610.5822.0416.0313.3625.3918.9415.86
Co-miningBackbone=ResNet-502026.04———16.0112.6210.3821.4716.2213.6124.118.2115.16
Co-studentBackbone=ResNet-502026.04———15.9912.6710.3823.0616.3913.4523.7118.1115.12
MonoDETR (Baseline)Backbone=ResNet-502026.04———11.178.737.5620.3615.2512.7622.7817.8314.97
MonoSAODBackbone=ResNet-502026.04———21.2815.612.7926.3118.8415.7126.6719.3716.25
SparseDetBackbone=ResNet-502026.04———16.9513.310.9721.9916.1313.4323.5818.3915.54