Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds
Author:
Affiliation:
1. National University of Defense Technology
2. University of Oxford
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9878378/9878366/09879147.pdf?arnumber=9879147
Reference61 articles.
1. From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network
2. PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud
3. End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
4. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;ruizhongtai qi;NeurIPS,2017
5. Pointnet: Deep learning on point sets for 3D classification and segmentation;qi;CVPR,2017
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