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Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale registration methods are rarely explored.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
Earlier work this paper cites.
An iterative image registration technique with an application to stereo vision
Bruce D Lucas, Takeo Kanade, et al · 1981
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Fast global registration
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2016
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
3dmatch: Learning local geometric descriptors from rgb-d reconstructions
Andy Zeng, Shuran Song, Matthias Nießner, Matthew Fisher, Jianxiong Xiao, and Thomas Funkhouser · 2017
Earlier work this paper cites.
Ppf-foldnet: Unsupervised learning of rotation invariant 3d local descriptors
Haowen Deng, Tolga Birdal, and Slobodan Ilic · 2018
Earlier work this paper cites.
Ppfnet: Global context aware local features for robust 3d point matching
Haowen Deng, Tolga Birdal, and Slobodan Ilic · 2018
Earlier work this paper cites.
Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2018
Earlier work this paper cites.
3dfeat-net: Weakly supervised local 3d features for point cloud registration
Zi Jian Yew and Gim Hee Lee · 2018
Earlier work this paper cites.
Pointnetlk: Robust & efficient point cloud registration using pointnet
Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan, and Simon Lucey · 2019
Earlier work this paper cites.
Fully convolutional geometric features
Christopher Choy, Jaesik Park, and Vladlen Koltun · 2019
Earlier work this paper cites.
Lo-net: Deep real-time lidar odometry
Qing Li, Shaoyang Chen, Cheng Wang, Xin Li, Chenglu Wen, Ming Cheng, and Jonathan Li · 2019
Earlier work this paper cites.
Deepvcp: An end-to-end deep neural network for point cloud registration
Weixin Lu, Guowei Wan, Yao Zhou, Xiangyu Fu, Pengfei Yuan, and Shiyu Song · 2019
Earlier work this paper cites.
Deep closest point: Learning representations for point cloud registration
Yue Wang and Justin M Solomon · 2019
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D3feat: Joint learning of dense detection and description of 3d local features
Xuyang Bai, Zixin Luo, Lei Zhou, Hongbo Fu, Long Quan, and Chiew-Lan Tai · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Deep global registration
Christopher Choy, Wei Dong, and Vladlen Koltun · 2020
Cited alongside, same era.
Feature-metric registration: A fast semi-supervised approach for robust point cloud registration without correspondences
Xiaoshui Huang, Guofeng Mei, and Jian Zhang · 2020
Cited alongside, same era.
Unsupervised learning of 3d scene flow from monocular camera
Guangming Wang, Xiaoyu Tian, Ruiqi Ding, and Hesheng Wang · 2021
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Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization
Guangming Wang, Xinrui Wu, Zhe Liu, and Hesheng Wang · 2021
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Cofinet: Reliable coarse-to-fine correspondences for robust pointcloud registration
Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, and Slobodan Ilic · 2021
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Deterministic point cloud registration via novel transformation decomposition
Wen Chen, Haoang Li, Qiang Nie, and Yun-Hui Liu · 2022
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Sc2-pcr: A second order spatial compatibility for efficient and robust point cloud registration
Zhi Chen, Kun Sun, Fan Yang, and Wenbing Tao · 2022
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Jiahao Li, Changhao Zhang, Ziyao Xu, Hangning Zhou, and Chi Zhang · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al · 2020
Cited alongside, same era.
Teaser: Fast and certifiable point cloud registration
Heng Yang, Jingnan Shi, and Luca Carlone · 2020
Cited alongside, same era.
Rpm-net: Robust point matching using learned features
Zi Jian Yew and Gim Hee Lee · 2020
Cited alongside, same era.
Spinnet: Learning a general surface descriptor for 3d point cloud registration
Sheng Ao, Qingyong Hu, Bo Yang, Andrew Markham, and Yulan Guo · 2021
Cited alongside, same era.
Pointdsc: Robust point cloud registration using deep spatial consistency
Xuyang Bai, Zixin Luo, Lei Zhou, Hongkai Chen, Lei Li, Zeyu Hu, Hongbo Fu, and Chiew-Lan Tai · 2021
Cited alongside, same era.
Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alex Schwing, and Alexander Kirillov · 2021
Cited alongside, same era.
Tianxin Huang, Jiangning Zhang, Jun Chen, Zhonggan Ding, Ying Tai, Zhenyu Zhang, Chengjie Wang, and Yong Liu · 2022
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Video swin transformer
Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, and Han Hu · 2022
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Geometric transformer for fast and robust point cloud registration
Zheng Qin, Hao Yu, Changjian Wang, Yulan Guo, Yuxing Peng, and Kai Xu · 2022
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What matters for 3d scene flow network
Guangming Wang, Yunzhe Hu, Zhe Liu, Yiyang Zhou, Masayoshi Tomizuka, Wei Zhan, and Hesheng Wang · 2022
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Residual 3-d scene flow learning with context-aware feature extraction
Guangming Wang, Yunzhe Hu, Xinrui Wu, and Hesheng Wang · 2022
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Sfgan: Unsupervised generative adversarial learning of 3d scene flow from the 3d scene self
Guangming Wang, Chaokang Jiang, Zehang Shen, Yanzi Miao, and Hesheng Wang · 2022
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Efficient 3d deep lidar odometry
Guangming Wang, Xinrui Wu, Shuyang Jiang, Zhe Liu, and Hesheng Wang · 2022
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Dcpcr: Deep compressed point cloud registration in large-scale outdoor environments
Louis Wiesmann, Tiziano Guadagnino, Ignacio Vizzo, Giorgio Grisetti, Jens Behley, and Cyrill Stachniss · 2022
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Regtr: End-to-end point cloud correspondences with transformers
Zi Jian Yew and Gim Hee Lee · 2022
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Global-pbnet: A novel point cloud registration for autonomous driving
Yuchao Zheng, Yujie Li, Shuo Yang, and Huimin Lu · 2022
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Translo: A window-based masked point transformer framework for large-scale lidar odometry
Jiuming Liu, Guangming Wang, Chaokang Jiang, Zhe Liu, and Hesheng Wang · 2023
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