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Abstract: 3D object detection from LiDAR data for autonomous driving has been making remarkable strides in recent years. Among the state-of-the-art methodologies, encoding point clouds into a bird's ...

Abstract: At present, with the original point cloud as input, most of the object detectors use Pointnet++ to extract features of the point cloud based on the Farthest Point Sampling (FPS). However, ...

These benefits lead to more flexible, maintainable, and efficient code structures. Unfortunately, Java does not natively support class extensions (categories) and there is a little chance such support ...

├── configs/ │ └── pointpillars.yaml │ ├── datasets/ │ └── nuscenes_dataset.py │ ├── models/ │ ├── pointpillars.py │ ├── pillar_encoder.py │ └── losses.py │ ├── utils ...