3D Object Detection for Autonomous Driving: A Comprehensive Survey

Author:

Mao Jiageng,Shi Shaoshuai,Wang Xiaogang,Li HongshengORCID

Funder

University Grants Committee

Innovation and Technology Commission - Hong Kong

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference390 articles.

1. Abu Alhaija, H., Mustikovela, S. K., Mescheder, L., Geiger, A., & Rother, C. (2018). Augmented reality meets computer vision: Efficient data generation for urban driving scenes. IJCV, 126, 961–972.

2. Aghdam, H. H., Heravi, E. J., Demilew, S. S., & Laganiere, R. (2021). Rad: Realtime and accurate 3D object detection on embedded systems. In CVPR.

3. Ali, W., Abdelkarim, S., Zidan, M., Zahran, M., & El Sallab. A. (2018). YOLO3D: End-to-end real-time 3D oriented object bounding box detection from lidar point cloud. In ECCVW.

4. Amini, A., Gilitschenski, I., Phillips, J., Moseyko, J., Banerjee, R., Karaman, S., & Rus, D. (2020). Learning robust control policies for end-to-end autonomous driving from data-driven simulation. IEEE RA-L, 5, 1143–1150.

5. Arnold, E., Al-Jarrah, O. Y., Dianati, M., Fallah, S., Oxtoby, D., & Mouzakitis, A. (2019). A survey on 3D object detection methods for autonomous driving applications. IEEE T-ITS, 20, 3782–3795.

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