[1] Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese. 3d semantic parsing of large-scale indoor spaces. In IEEE Conf. Comput. Vis. Pattern Recog., pages 1534-1543, 2016. 2, 6, 7
[2] Xuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang, Yilun Chen, Hongbo Fu, and Chiew-Lan Tai. Transfusion: Robust lidar-camera fusion for 3d object detection with transformers. In IEEE Conf. Comput. Vis. Pattern Recog., pages 1090-1099, 2022. 16
[3] Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyril Stachniss, and Jurgen Gall. Semantickitti: A dataset for semantic scene understanding of lidar sequences. In Int. Conf. Comput. Vis., pages 9297-9307, 2019. 15
[4] 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 IEEE Conf. Comput. Vis. Pattern Recog., pages 11621-11631, 2020. 15
[5] Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J Guibas, Jonathan Tremblay, Sameh Khamis, et al. Efficient geometry-aware 3d generative adversarial networks. In IEEE Conf. Comput. Vis. Pattern Recog., pages 16123-16133, 2022. 2
[6] Jintai Chen, Biwen Lei, Qingyu Song, Haochao Ying, Danny Z Chen, and Jian Wu. A hierarchical graph network for 3d object detection on point clouds. In IEEE Conf. Comput. Vis. Pattern Recog., pages 392-401, 2020. 9
[7] Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia. Multi-view 3d object detection network for autonomous driving. In IEEE Conf. Comput. Vis. Pattern Recog., pages 1907-1915, 2017. 1, 3
[8] Yukang Chen, Jianhui Liu, Xiaojuan Qi, Xiangyu Zhang, Jian Sun, and Jiaya Jia. Scaling up kernels in 3d cnns. Adv. Neural Inform. Process. Syst., 2022, 7, 10, 15
[9] Bowen Cheng, Lu Sheng, Shaoshuai Shi, Ming Yang, and Dong Xu. Back-tracing representative points for voting-based 3d object detection in point clouds. In IEEE Conf. Comput. Vis. Pattern Recog., pages 8963-8972, 2021. 9
[10] Ran Cheng, Ryan Razani, Ehsan Taghavi, Enxu Li, and Bingbing Liu. 2-s3net: Attentive feature fusion with adaptive feature selection for sparse semantic segmentation network. In IEEE Conf. Comput. Vis. Pattern Recog., 2021. 16
[11] Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu, and Winston H Hsu. A unified point-based framework for 3d segmentation. In Int. Conf. 3D Vis., pages 155-163. IEEE, 2019. 7
[12] Christopher Choy, JunYoung Gwak, and Silvio Savarese. 4d spatio-temporal convnets: Minkowski convolutional neural networks. In IEEE Conf. Comput. Vis. Pattern Recog., pages 3075-3084, 2019. 1, 3, 7
[13] Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, and Chunhua Shen. Twins: Revisiting the design of spatial attention in vision transformers. Adv. Neural Inform. Process. Syst., 34:9355-9366, 2021. 1
[14] Tiago Cortinhal, George Tzelepis, and Eren Erdal Aksoy. Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds. In International Symposium on Visual Computing, 2020. 16
[15] Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner. Scannet: Richly-annotated 3d reconstructions of indoor scenes. In IEEE Conf. Comput. Vis. Pattern Recog., 2017. 1, 2, 6
[16] Angela Dai and Matthias Nießner. 3dmv: Joint 3d-multi-view prediction for 3d semantic scene segmentation. In Eur. Conf. Comput. Vis., pages 452-468, 2018. 7
[17] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805, 2018. 1
[18] Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Weiming Zhang, Nenghai Yu, Lu Yuan, Dong Chen, and Baining Guo. Cswin transformer: A general vision transformer backbone with cross-shaped windows. In IEEE Conf. Comput. Vis. Pattern Recog., pages 12124-12134, 2022. 1, 2, 3
[19] Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929, 2020. 1, 2, 3, 4
[20] Lue Fan, Ziqi Pang, Tianyuan Zhang, Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang. Embracing single stride 3d object detector with sparse transformer. In IEEE Conf. Comput. Vis. Pattern Recog., pages 8458-8468, 2022. 3
[21] Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten. 3d semantic segmentation with submanifold sparse convolutional networks. In IEEE Conf. Comput. Vis. Pattern Recog., pages 9224-9232, 2018. 3, 7, 16
[22] Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Xinghao Chen, Yunhe Wang, and Chang Xu. Cmt: Convolutional neural networks meet vision transformers. In IEEE Conf. Comput. Vis. Pattern Recog., pages 12175-12185, 2022. 1, 2, 3