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NVIDIA
NVIDIA
PointPillarNet
Model
NVIDIA
NVIDIA
PointPillarNet

Model to detect one or more objects from a LIDAR point cloud file and return 3D bounding boxes.

This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
Intended Application(s) & Domain(s):Classifying cyclists, persons, and vehicles.
Model Type:Object Detection
Intended Users:Developers working in industrial, robotics, and smart space applications.
Output:3-D Bounding Box(es), Category Label(s), Confidence Score(s)
Describe how the model works:Detects one or more objects from a LIDAR point cloud file and returns a 3D bounding box and confidence score for each object.
Technical Limitations:PointPillarNet does not give good results for very crowded traffic scenes.
Verified to have met prescribed NVIDIA standards:Yes
Performance Metrics:Accuracy, Mean Average Precision (mAP), Recall
Potential Known Risks:Model may fail to detect classifying objects.
Licensing:https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/