tsinghua-rll/VoxelNet-tensorflow
A TensorFlow implementation of VoxelNet for 3D object detection in point clouds from LiDAR sensors.
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This repository provides a TensorFlow implementation of the VoxelNet architecture for 3D object detection in autonomous driving scenarios. The system processes 3D point cloud data from Velodyne sensors to detect objects like cars and pedestrians. It includes a VFE (Voxel Feature Encoding) layer and an RPN (Region Proposal Network) for region-based detection, with support for data augmentation during training.
Frequently asked
- What is tsinghua-rll/VoxelNet-tensorflow?
- A TensorFlow implementation of VoxelNet for 3D object detection in point clouds from LiDAR sensors.
- Is VoxelNet-tensorflow open source?
- Yes — tsinghua-rll/VoxelNet-tensorflow is open source, released under the MIT license.
- What language is VoxelNet-tensorflow written in?
- tsinghua-rll/VoxelNet-tensorflow is primarily written in Python.
- How popular is VoxelNet-tensorflow?
- tsinghua-rll/VoxelNet-tensorflow has 466 stars on GitHub.
- Where can I find VoxelNet-tensorflow?
- tsinghua-rll/VoxelNet-tensorflow is on GitHub at https://github.com/tsinghua-rll/VoxelNet-tensorflow.