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Pseudo-label based self training approaches are a popular method for source-free unsupervised domain adaptation.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and H. Valpola · 2017
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Cross-domain weakly-supervised object detection through progressive domain adaptation
Naoto Inoue, Ryosuke Furuta, T. Yamasaki, and K. Aizawa · 2018
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Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
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Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Ipod: Intensive point-based object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Exploring object relation in mean teacher for cross-domain detection
Qi Cai, Yingwei Pan, C. Ngo, Xinmei Tian, Ling yu Duan, and Ting Yao · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Multi-task multi-sensor fusion for 3d object detection
Ming Liang, Bin Yang, Yun Chen, Rui Hu, and Raquel Urtasun · 2019
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Pointdan: A multi-scale 3d domain adaption network for point cloud representation
Can Qin, Haoxuan You, Lichen Wang, C.-C. Jay Kuo, and Y. Fu · 2019
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Domain adaptation for object detection via style consistency
Adrian Lopez Rodriguez and K. Mikolajczyk · 2019
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Pointrcnn: 3d object proposal generation and detection from point cloud
Train in germany, test in the usa: Making 3d object detectors generalize
Yan Wang, Xiangyu Chen, Yurong You, Li Erran, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao · 2020
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Train in germany, test in the usa: Making 3d object detectors generalize
Yan Wang, X. Chen, Yurong You, Li Erran, Bharath Hariharan, M. Campbell, Kilian Q. Weinberger, and Wei-Lun Chao · 2020
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3dssd: Point-based 3d single stage object detector
Zetong Yang, Yanan Sun, Shu Liu, and Jiaya Jia · 2020
Later among the works it cites.
Pseudo-labeling for scalable 3d object detection
Benjamin Caine, R. Roelofs, Vijay Vasudevan, Jiquan Ngiam, Yuning Chai, Z. Chen, and Jonathon Shlens · 2021
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Velat Kilic, Deepti Hegde, Vishwanath Sindagi, A. Brinton Cooper, Mark A. Foster, and Vishal M. Patel · 2021
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Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Q. Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Cited alongside, same era.
Structure aware single-stage 3d object detection from point cloud
Chenhang He, Hui Zeng, Jianqiang Huang, Xian-Sheng Hua, and Lei Zhang · 2020
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xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation
M. Jaritz, T. Vu, R. de Charette, E. Wirbel, and P. Perez · 2020
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Universal source-free domain adaptation
Jogendra Nath Kundu, Naveen Venkat, V. RahulM., and R. Venkatesh Babu · 2020
Cited alongside, same era.
Sf-uda3d: Source-free unsupervised domain adaptation for lidar-based 3d object detection
Cristiano Saltori, St’ephane Lathuili’ere, N. Sebe, E. Ricci, and Fabio Galasso · 2020
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Cited alongside, same era.
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A free lunch for unsupervised domain adaptive object detection without source data
Xianfeng Li, Weijie Chen, Di Xie, Shicai Yang, Peng Yuan, Shiliang Pu, and Yueting Zhuang · 2021
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Adversarial unsupervised domain adaptation for 3d semantic segmentation with multi-modal learning
Wei Liu, Zhiming Luo, Yuanzheng Cai, Ying Yu, Yang Ke, José Marcato Junior, Wesley Nunes Gonçalves, and Jonathan Li · 2021
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Unbiased teacher for semi-supervised object detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, and Peter Vajda · 2021
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Unsupervised domain adaptive 3d detection with multi-level consistency, 2021
Zhipeng Luo, Zhongang Cai, Changqing Zhou, Gongjie Zhang, Haiyu Zhao, Shuai Yi, Shijian Lu, Hongsheng Li, Shanghang Zhang, and Ziwei Liu · 2021
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Unsupervised domain adaptation of object detectors: A survey, 2021
Poojan Oza, Vishwanath A. Sindagi, Vibashan VS, and Vishal M. Patel · 2021
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Canadian adverse driving conditions dataset
Matthew Pitropov, Danson Evan Garcia, Jason Rebello, Michael Smart, Carlos Wang, Krzysztof Czarnecki, and Steven Waslander · 2021
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St3d: Self-training for unsupervised domain adaptation on 3d object detection
Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, and Xiaojuan Qi · 2021
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