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CenterPoint

CenterPoint is a LiDAR-based 3D object detection model integrated under the detection3d task namespace. It uses a PointPillars-style frontend with a SECOND backbone, SECONDFPN neck, and CenterPoint detection head.

Summary

Property Value
Task 3D object detection
Modality LiDAR
Input Point cloud
Output 3D bounding boxes and class scores
Architecture PointPillars + SECOND + SECONDFPN + head
Datasets NuScenes, T4Dataset

Available Configurations

Config Name Dataset Purpose
detection3d/centerpoint/voxel020_second_secfpn_51m_nuscenes NuScenes Standard NuScenes 51 m configuration
detection3d/centerpoint/voxel024_second_secfpn_120m_t4dataset_j6gen2 T4Dataset 120 m T4Dataset configuration (aligned with TransFusion)

Training

autoware-ml train --config-name detection3d/centerpoint/voxel020_second_secfpn_51m_nuscenes
autoware-ml train --config-name detection3d/centerpoint/voxel024_second_secfpn_120m_t4dataset_j6gen2

For a pipeline validation run:

autoware-ml train \
    --config-name detection3d/centerpoint/voxel020_second_secfpn_51m_nuscenes \
    +trainer.fast_dev_run=true

Evaluation

autoware-ml test \
    --config-name detection3d/centerpoint/voxel020_second_secfpn_51m_nuscenes \
    --weights mlruns/detection3d/centerpoint/voxel020_second_secfpn_51m_nuscenes/<run_id>/artifacts/checkpoints/best.ckpt

Deployment

autoware-ml deploy \
    --config-name detection3d/centerpoint/voxel024_second_secfpn_120m_t4dataset_j6gen2 \
    --weights mlruns/detection3d/centerpoint/voxel024_second_secfpn_120m_t4dataset_j6gen2/<run_id>/artifacts/checkpoints/best.ckpt

The export produces the two ONNX modules consumed by autoware_universe/perception/autoware_lidar_centerpoint: pts_voxel_encoder_centerpoint.onnx encodes decorated pillar features into per-pillar descriptors, and pts_backbone_neck_head_centerpoint.onnx predicts the raw dense detection heads (heatmap, reg, height, dim, rot, vel) from the scattered BEV canvas. Voxelization, pillar decoration, BEV scatter, and box decoding all run in the runtime node.

Implementation

Path Description
autoware_ml/models/detection3d/centerpoint.py CenterPoint model wrapper
autoware_ml/models/detection3d/encoders/pillar.py Pillar encoder and scatter
autoware_ml/models/detection3d/backbones/second.py SECOND backbone
autoware_ml/models/detection3d/necks/second_fpn.py SECONDFPN neck
autoware_ml/models/detection3d/heads/centerpoint.py CenterPoint detection head
autoware_ml/preprocessing/detection3d/point_pillar.py Pillar preprocessing
autoware_ml/datamodule/nuscenes/detection3d.py NuScenes datamodule
autoware_ml/datamodule/t4dataset/detection3d.py T4Dataset datamodule
autoware_ml/configs/tasks/detection3d/centerpoint/ Task configurations

Acknowledgment

The Autoware-ML CenterPoint implementation was ported from the official mmdetection3d project by OpenMMLab.