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MODEL ZOO

Common settings and notes

  • The experiments are run with PyTorch 1.1, CUDA 10.0, and CUDNN 7.5.
  • The training is conducted on 4 V100 GPUs in a DGX server.
  • Testing times are measured on a TITAN RTX GPU with batch size 1.

nuScenes 3D Detection

We provide training / validation configurations, logs, pretrained models, and prediction files for all models in the paper

VoxelNet

Model FPS Validation MAP Validation NDS Link
centerpoint_voxel_1024 16 56.4 64.8 URL
centerpoint_voxel_1440_dcn 11 57.1 65.4 URL
centerpoint_voxel_1440_dcn(flip) 3 59.5 67.4 URL

PointPillars

Model FPS Validation MAP Validation NDS Link
centerpoint_pillar 31 50.3 60.2 URL

nuScenes 3D Tracking

Model Tracking time Total time Validation AMOTA ↑ Validation AMOTP ↓ Link
centerpoint_voxel_1024 1ms 64ms 63.7 0.606 URL
centerpoint_voxel_1440_dcn 1ms 95ms 64.1 0.596 URL
centerpoint_voxel_1440_dcn(flip test) 1ms 343ms 66.5 0.567 URL

nuScenes test set Detection/Tracking

Detection

Model Test MAP Test NDS Link
centerpoint_voxel_1440_dcn 58.0 65.5 Detection

Tracking

Model Test AMOTA Test AMOTP Link
centerpoint_voxel_1440_dcn(flip test) 63.8* 0.555* Tracking

*The numbers are from an old version of the codebase. Current model should perform slightly better.

Enhanced Results

This section aims to keep track of follow-up works based on CenterPoint. We appreciate all contributions and please send us an email if you want to be listed here.

Method Val mAP Val NDS Val AMOTA Test mAP Test NDS Test AMOTA