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Model
Model to detect one or more objects from a LIDAR point cloud file and return 3D bounding boxes.
Use the NGC CLI to download:
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| Field | Response |
|---|---|
| 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/ |