sshaoshuai/PointRCNN
PointRCNN is a two-stage 3D object detector that generates and refines 3D bounding box proposals directly from raw point cloud data.
Not currently ranked — collecting fresh signals.
star history
This repository implements the PointRCNN model from CVPR 2019, which uses a bottom-up approach to generate 3D object proposals from raw point clouds. The first stage produces proposals in a canonical coordinate system using a bin-based regression loss, and the second stage refines these proposals. It leverages PointNet++ for point cloud feature extraction and achieves state-of-the-art results on the KITTI 3D object detection benchmark.
Frequently asked
- What is sshaoshuai/PointRCNN?
- PointRCNN is a two-stage 3D object detector that generates and refines 3D bounding box proposals directly from raw point cloud data.
- Is PointRCNN open source?
- Yes — sshaoshuai/PointRCNN is open source, released under the MIT license.
- What language is PointRCNN written in?
- sshaoshuai/PointRCNN is primarily written in Python.
- How popular is PointRCNN?
- sshaoshuai/PointRCNN has 1.8k stars on GitHub.
- Where can I find PointRCNN?
- sshaoshuai/PointRCNN is on GitHub at https://github.com/sshaoshuai/PointRCNN.