[10] Fangzhou Hong, Lingdong Kong, Hui Zhou, Xinge Zhu, Hongsheng Li, and Ziwei Liu. Unified 3d and 4d panoptic segmentation via dynamic shifting network. arXiv preprint arXiv:2203.07186, 2022.
[11] Runnan Chen, Xinge Zhu, Nenglun Chen, Wei Li, Yuexin Ma, Ruigang Yang, and Wenping Wang. Zero-shot point cloud segmentation by transferring geometric primitives. arXiv preprint arXiv:2210.09923, 2022.
[12] Björn Michele, Alexandre Boulch, Gilles Puy, Maxime Bucher, and Renaud Marlet. Generative zero-shot learning for semantic segmentation of 3d point clouds. In International Conference on 3D Vision, pages 992-1002, 2021.
[13] Yueh-Cheng Liu, Yu-Kai Huang, Hung-Yueh Chiang, Hung-Ting Su, Zhe-Yu Liu, Chin-Tang Chen, Ching-Yu Tseng, and Winston H Hsu. Learning from 2d: Contrastive pixel-to-point knowledge transfer for 3d pretraining. arXiv preprint arXiv:2104.04687, 2021.
[14] Coretin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, and Renaud Marlet. Image-to-lidar self-supervised distillation for autonomous driving data. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 9891-9901, 2022.
[15] Lingdong Kong, Jiawei Ren, Liang Pan, and Ziwei Liu. Lasermix for semi-supervised lidar semantic segmentation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 21705-21715, 2023.
[16] Lingdong Kong, Niamul Quader, and Venice Erin Liong. Conda: Unsupervised domain adaptation for lidar segmentation via regularized domain concatenation. In IEEE International Conference on Robotics and Automation, pages 9338-9345, 2023.
[17] Runnan Chen, Youquan Liu, Lingdong Kong, Xinge Zhu, Yuexin Ma, Yikang Li, Yuenan Hou, Yu Qiao, and Wenping Wang. Clip2scene: Towards label-efficient 3d scene understanding by clip. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 7020-7030, 2023.
[18] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. Learning transferable visual models from natural language supervision. In International Conference on Machine Learning, pages 8748-8763. PMLR, 2021.
[19] Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dólar, and Ross Girshick. Segment anything. In IEEE/CVF International Conference on Computer Vision, pages 4015-4026, 2023.
[20] Chong Zhou, Chen Change Loy, and Bo Dai. Extract free dense labels from clip. In European Conference on Computer Vision, pages 696-712, 2022.
[21] Yiteng Xu, Peishan Cong, Yichen Yao, Runnan Chen, Yuenan Hou, Xinge Zhu, Xuming He, Jingyi Yu, and Yuexin Ma. Human-centric scene understanding for 3d large-scale scenarios. In IEEE/CVF International Conference on Computer Vision, pages 20349-20359, 2023.
[22] Youquan Liu, Runnan Chen, Xin Li, Lingdong Kong, Yuchen Yang, Zhaoyang Xia, Yeqi Bai, Xinge Zhu, Yuexin Ma, Yikang Li, et al. Uniseg: A unified multi-modal lidar segmentation network and the openpcseg codebase. In IEEE/CVF International Conference on Computer Vision, pages 21662-21673, 2023.
[23] Bowen Cheng, Alex Schwing, and Alexander Kirillov. Per-pixel classification is not all you need for semantic segmentation. Advances in Neural Information Processing Systems, 34:17864-17875, 2021.
[24] Robin Strudel, Ricardo Garcia, Ivan Laptev, and Cordelia Schmid. Segmenter: Transformer for semantic segmentation. In IEEE/CVF International Conference on Computer Vision, pages 7262-7272, 2021.
[25] Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar. Masked-attention mask transformer for universal image segmentation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1290–1299, 2022.
[26] René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun. Vision transformers for dense prediction. In IEEE/CVF International Conference on Computer Vision, pages 12179-12188, 2021.
[27] Wenhai Wang, Jifeng Dai, Zhe Chen, Zhenhang Huang, Zhiqi Li, Xizhou Zhu, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, et al. Internimage: Exploring large-scale vision foundation models with deformable convolutions. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 14408-14419, 2022.