MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views-Reference-Cited by-同舟云学术

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MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views

Published:2020-10-24 Issue: Volume: Page:
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Container-title:2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Chen Ke,Oldja Ryan,Smolyanskiy Nikolai,Birchfield Stan,Popov Alexander,Wehr David,Eden Ibrahim,Pehserl Joachim

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9340668/9340635/09341450.pdf?arnumber=9341450

Cited by 21 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. Exploring Contextual Representation and Multi-modality for End-to-end Autonomous Driving;Engineering Applications of Artificial Intelligence;2024-09

2. Beyond traditional visual object tracking: a survey;International Journal of Machine Learning and Cybernetics;2024-08-26

3. LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation;IEEE Transactions on Multimedia;2024

4. Vehicle Detection for Autonomous Driving: A Review of Algorithms and Datasets;IEEE Transactions on Intelligent Transportation Systems;2023-11

5. Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles;Soft Computing;2023-10-03

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