High Dimensional Frustum PointNet for 3D Object Detection from Camera, LiDAR, and Radar-Reference-Cited by-同舟云学术

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High Dimensional Frustum PointNet for 3D Object Detection from Camera, LiDAR, and Radar

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Wang Leichen,Chen Tianbai,Anklam Carsten,Goldluecke Bastian

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9304518/9304528/09304655.pdf?arnumber=9304655

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Malicious Attacks against Multi-Sensor Fusion in Autonomous Driving;Proceedings of the 30th Annual International Conference on Mobile Computing and Networking;2024-05-29

2. LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object Detection;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Morphological estimation of primary branch length of individual apple trees during the deciduous period in modern orchard based on PointNet++;Computers and Electronics in Agriculture;2024-05

4. Sparsity-Robust Feature Fusion for Vulnerable Road-User Detection with 4D Radar;Applied Sciences;2024-03-26

5. Implementation of Object Detection for Autonomous Vehicles by LiDAR and Camera Fusion;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

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