[1] Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom. nuscenes: A multimodal dataset for autonomous driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 11621-11631, 2020. 2, 3, 4, 7, 17
[2] Runjian Chen, Yao Mu, Runsen Xu, Wenqi Shao, Chenhan Jiang, Hang Xu, Zhenguo Li, and Ping Luo. Co^3: Cooperative unsupervised 3d representation learning for autonomous driving. arXiv preprint arXiv:2206.04028, 2022. 3
[3] Jiajun Deng, Shaoshuai Shi, Peiwei Li, Wengang Zhou, Yanyong Zhang, and Houqiang Li. Voxel r-cnn: Towards high performance voxel-based 3d object detection. In Proceedings of the AAAI Conference on Artificial Intelligence, pages 1201-1209, 2021. 6
[4] Shengheng Deng, Zhihao Liang, Lin Sun, and Kui Jia. Vista: Boosting 3d object detection via dual cross-view spatial attention. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8448-8457, 2022. 3
[5] Andreas Geiger, Philip Lenz, and Raquel Urtasun. Are we ready for autonomous driving? the kitti vision benchmark suite. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 3354-3361, 2012. 3, 7, 17
[6] Georg Hess, Johan Jaxing, Elias Svensson, David Hagerman, Christoffer Petersson, and Lennart Svensson. Masked autoencoder for self-supervised pre-training on lidar point clouds. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 350-359, 2023. 1, 3, 7
[7] Siyuan Huang, Yichen Xie, Song-Chun Zhu, and Yixin Zhu. Spatio-temporal self-supervised representation learning for 3d point clouds. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 6535-6545, 2021. 3, 8
[8] KJ Joseph, Salman Khan, Fahad Shahbaz Khan, and Vineeth N Balasubramanian. Towards open world object detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 5830-5840, 2021. 6
[9] Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al. Segment anything. arXiv preprint arXiv:2304.02643, 2023. 5
[10] Georg Krispel, David Schinagl, Christian Fruhwirth-Reisinger, Horst Possegger, and Horst Bischof. Maeli-masked autoencoder for large-scale lidar point clouds. arXiv preprint arXiv:2212.07207, 2022. 3
[11] 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, pages 12697-12705, 2019. 3
[12] Hanxue Liang, Chenhan Jiang, Dapeng Feng, Xin Chen, Hang Xu, Xiaodan Liang, Wei Zhang, Zhenguo Li, and Luc Van Gool. Exploring geometry-aware contrast and clustering harmonization for self-supervised 3d object detection. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3293-3302, 2021. 3, 7, 8
[13] Zhiwei Lin and Yongtao Wang. Bev-mae: Bird's eye view masked autoencoders for outdoor point cloud pre-training. arXiv preprint arXiv:2212.05758, 2022. 3, 7, 8, 18
[14] Jiageng Mao, Minzhe Niu, Chenhan Jiang, Hanxue Liang, Jingheng Chen, Xiaodan Liang, Yamin Li, Chaoqiang Ye, Wei Zhang, Zhenguo Li, et al. One million scenes for autonomous driving: Once dataset. arXiv preprint arXiv:2106.11037, 2021. 2, 7, 16