19. 19
Dataset: WAYMO Open Dataset[6]
Model: PointPillars[7], Range Sparse Net(RSN)[8]
3D OBJECT DETECTION
20. 20
[1] Zhaoqi Leng, Mingxing Tan ~Mingxing_Tan3 , Chenxi Liu, Ekin Dogus Cubuk, Jay
Shi, Shuyang Cheng, Dragomir Anguelov. PolyLoss: A Polynomial Expansion
Perspective of Classification Loss Functions. In ICLR 2022.
[2] Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. Imagenet: A
large-scale hierarchical image database. In 2009 IEEE conference on computer vision
and pattern recognition, pp. 248–255. Ieee, 2009.
[3] Mingxing Tan and Quoc V Le. Efficientnetv2: Smaller models and faster training.
In International Conference on Machine Learning, 2021.
[4] Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva
Ramanan, Piotr Dollar, and C Lawrence Zitnick. Microsoft coco: Common objects in
context. In ´ European conference on computer vision, pp. 740–755. Springer, 2014.
[5] Kaiming He, Georgia Gkioxari, Piotr Dollar, and Ross Girshick. Mask r-cnn. In ´
Proceedings of the IEEE international conference on computer vision, pp. 2961–2969,
2017.
Reference
21. 21
[6] Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai
Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al.
Scalability in perception for autonomous driving: Waymo open dataset. In
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
Recognition, pp. 2446–2454, 2020.
[7] Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar
Beijbom. Pointpillars: Fast encoders for object detection from point clouds. In
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
Recognition, pp. 12697–12705, 2019.
[8] Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang,
Christian Sminchisescu, and Dragomir Anguelov. Rsn: Range sparse net for efficient,
accurate lidar 3d object detection. In Proceedings of the IEEE/CVF Conference on
Computer Vision and Pattern Recognition, 2021.
Reference