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Label-efficient LiDAR-based 3D object detection is currently dominated by weakly/semi-supervised methods.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Efficient l-shape fitting for vehicle detection using laser scanners
Xiao Zhang, Wenda Xu, Chiyu Dong, and John M Dolan · 2017
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Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 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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Hybrid task cascade for instance segmentation
Kai Chen, Jiangmiao Pang, Jiaqi Wang, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jianping Shi, Wanli Ouyang, et al · 2019
Earlier work this paper cites.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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MMDetection3D: OpenMMLab next-generation platform for general 3D object detection
MMDetection3D Contributors · 2020
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Weakly supervised 3d object detection from lidar point cloud
Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, and Dengxin Dai · 2020
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Weakly supervised 3d object detection from point clouds
Zengyi Qin, Jinglu Wang, and Yan Lu · 2020
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Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin A Raffel, Ekin Dogus Cubuk, Alexey Kurakin, and Chun-Liang Li · 2020
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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
Earlier work this paper cites.
Openpcdet: An open-source toolbox for 3d object detection from point clouds
OpenPCDet Development Team · 2020
Cited alongside, same era.
Pointcontrast: Unsupervised pre-training for 3d point cloud understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas Guibas, and Or Litany · 2020
Cited alongside, same era.
3dssd: Point-based 3d single stage object detector
Zetong Yang, Yanan Sun, Shu Liu, and Jiaya Jia · 2020
Cited alongside, same era.
Sess: Self-ensembling semi-supervised 3d object detection
Na Zhao, Tat-Seng Chua, and Gim Hee Lee · 2020
Cited alongside, same era.
Lidar r-cnn: An efficient and universal 3d object detector
Zhichao Li, Feng Wang, and Naiyan Wang · 2021
Cited alongside, same era.
Towards a weakly supervised framework for 3d point cloud object detection and annotation
Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Yunde Jia, and Luc Van Gool · 2021
Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking
Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado, Lubing Zhou, Holger Caesar, Oscar Beijbom, and Abhinav Valada · 2022
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Smac-seg: Lidar panoptic segmentation via sparse multi-directional attention clustering
Enxu Li, Ryan Razani, Yixuan Xu, and Bingbing Liu · 2022
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Less: Label-efficient semantic segmentation for lidar point clouds
Minghua Liu, Yin Zhou, Charles R Qi, Boqing Gong, Hao Su, and Dragomir Anguelov · 2022
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Scribble-supervised lidar semantic segmentation
Ozan Unal, Dengxin Dai, and Luc Van Gool · 2022
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Sparse cross-scale attention network for efficient lidar panoptic segmentation
Shuangjie Xu, Rui Wan, Maosheng Ye, Xiaoyi Zou, and Tongyi Cao · 2022
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Super sparse 3d object detection
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Cited alongside, same era.
Offboard 3d object detection from point cloud sequences
Charles R. Qi, Yin Zhou, Mahyar Najibi, Pei Sun, Khoa Vo, Boyang Deng, and Dragomir Anguelov · 2021
Cited alongside, same era.
Gp-s3net: Graph-based panoptic sparse semantic segmentation network
Ryan Razani, Ran Cheng, Enxu Li, Ehsan Taghavi, Yuan Ren, and Liu Bingbing · 2021
Cited alongside, same era.
3dioumatch: Leveraging iou prediction for semi-supervised 3d object detection
He Wang, Yezhen Cong, Or Litany, Yue Gao, and Leonidas J Guibas · 2021
Cited alongside, same era.
Auto4d: Learning to label 4d objects from sequential point clouds
Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, and Raquel Urtasun · 2021
Cited alongside, same era.
Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl · 2021
Cited alongside, same era.
Panoptic-polarnet: Proposal-free lidar point cloud panoptic segmentation
Zixiang Zhou, Yang Zhang, and Hassan Foroosh · 2021
Cited alongside, same era.
Lue Fan, Yuxue Yang, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang · 2023
Later among the works it cites.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
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Center focusing network for real-time lidar panoptic segmentation
Xiaoyan Li, Gang Zhang, Boyue Wang, Yongli Hu, and Baocai Yin · 2023
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Detzero: Rethinking offboard 3d object detection with long-term sequential point clouds
Tao Ma, Xuemeng Yang, Hongbin Zhou, Xin Li, Botian Shi, Junjie Liu, Yuchen Yang, Zhizheng Liu, Liang He, Yu Qiao, Yikang Li, and Hongsheng Li · 2023
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Pv-rcnn++: Point-voxel feature set abstraction with local vector representation for 3d object detection
Shaoshuai Shi, Li Jiang, Jiajun Deng, Zhe Wang, Chaoxu Guo, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2023
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Coin: Contrastive instance feature mining for outdoor 3d object detection with very limited annotations
Qiming Xia, Jinhao Deng, Chenglu Wen, Hai Wu, Shaoshuai Shi, Xin Li, and Cheng Wang · 2023
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Mv-jar: Masked voxel jigsaw and reconstruction for lidar-based self-supervised pre-training
Runsen Xu, Tai Wang, Wenwei Zhang, Runjian Chen, Jinkun Cao, Jiangmiao Pang, and Dahua Lin · 2023
Later among the works it cites.