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Traditional LiDAR-based object detection research primarily focuses on closed-set scenarios, which falls short in complex real-world applications.
Mitigating the hubness problem for zero-shot learning of 3d objects
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 1907
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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
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Seeded region growing
Rolf Adams and Leanne Bischof · 1994
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On the segmentation of 3d lidar point clouds
Bertrand Douillard, James Underwood, Noah Kuntz, Vsevolod Vlaskine, Alastair Quadros, Peter Morton, and Alon Frenkel · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 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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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Zero-shot learning of 3d point cloud objects
Ali Cheraghian, Shafin Rahman, and Lars Petersson · 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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Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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Complexer-yolo: Real-time 3d object detection and tracking on semantic point clouds
Martin Simon, Karl Amende, Andrea Kraus, Jens Honer, Timo Samann, Hauke Kaulbersch, Stefan Milz, and Horst Michael Gross · 2019
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Mvx-net: Multimodal voxelnet for 3d object detection
Vishwanath A Sindagi, Yin Zhou, and Oncel Tuzel · 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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Transductive zero-shot learning for 3d point cloud classification
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 2020
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MMDetection3D: OpenMMLab next-generation platform for general 3D object detection
MMDetection3D Contributors · 2020
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Deep learning for 3d point clouds: A survey
Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, and Mohammed Bennamoun · 2020
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Epnet: Enhancing point features with image semantics for 3d object detection
Tengteng Huang, Zhe Liu, Xiwu Chen, and Xiang Bai · 2020
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Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 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.
Pillar-based object detection for autonomous driving
Yue Wang, Alireza Fathi, Abhijit Kundu, David A Ross, Caroline Pantofaru, Tom Funkhouser, and Justin Solomon · 2020
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Identifying unknown instances for autonomous driving
3dos: Towards 3d open set learning-benchmarking and understanding semantic novelty detection on point clouds
Antonio Alliegro, Francesco Cappio Borlino, and Tatiana Tommasi · 2022
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Transfusion: Robust lidar-camera fusion for 3d object detection with transformers
Xuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang, Yilun Chen, Hongbo Fu, and Chiew-Lan Tai · 2022
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Open-world semantic segmentation for lidar point clouds
Jun Cen, Peng Yun, Shiwei Zhang, Junhao Cai, Di Luan, Mingqian Tang, Ming Liu, and Michael Yu Wang · 2022
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Zero-shot learning on 3d point cloud objects and beyond
Ali Cheraghian, Shafin Rahman, Townim F Chowdhury, Dylan Campbell, and Lars Petersson · 2022
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Open-vocabulary object detection via vision and language knowledge distillation
Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, and Yin Cui · 2022
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Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, and Raquel Urtasun · 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.
3d-cvf: Generating joint camera and lidar features using cross-view spatial feature fusion for 3d object detection
Jin Hyeok Yoo, Yecheol Kim, Jisong Kim, and Jun Won Choi · 2020
Cited alongside, same era.
A survey of autonomous driving: Common practices and emerging technologies
Ekim Yurtsever, Jacob Lambert, Alexander Carballo, and Kazuya Takeda · 2020
Cited alongside, same era.
End-to-end multi-view fusion for 3d object detection in lidar point clouds
Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, and Vijay Vasudevan · 2020
Cited alongside, same era.
Open-set 3d object detection
Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, and Ming Liu · 2021
Cited alongside, same era.
Rangedet: In defense of range view for lidar-based 3d object detection
Lue Fan, Xuan Xiong, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang · 2021
Cited alongside, same era.
Tingting Liang, Hongwei Xie, Kaicheng Yu, Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Tao Tang, Bing Wang, and Zhi Tang · 2022
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Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation
Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, and Song Han · 2022
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Simple open-vocabulary object detection with vision transformers
Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, et al · 2022
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Openscene: 3d scene understanding with open vocabularies
Songyou Peng, Kyle Genova, Chiyu Jiang, Andrea Tagliasacchi, Marc Pollefeys, Thomas Funkhouser, et al · 2022
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Detclip: Dictionary-enriched visual-concept paralleled pre-training for open-world detection
Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu, Wei Zhang, Zhenguo Li, Chunjing Xu, and Hang Xu · 2022
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Open-vocabulary detr with conditional matching
Yuhang Zang, Wei Li, Kaiyang Zhou, Chen Huang, and Chen Change Loy · 2022
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Detecting twenty-thousand classes using image-level supervision
Xingyi Zhou, Rohit Girdhar, Armand Joulin, Philipp Krähenbühl, and Ishan Misra · 2022
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Pointclip v2: Prompting clip and gpt for powerful 3d open-world learning
Xiangyang Zhu, Renrui Zhang, Bowei He, Ziyu Guo, Ziyao Zeng, Zipeng Qin, Shanghang Zhang, and Peng Gao · 2022
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Yang Cao, Yihan Zeng, Hang Xu, and Dan Xu · 2023
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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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Logonet: Towards accurate 3d object detection with local-to-global cross-modal fusion
Xin Li, Tao Ma, Yuenan Hou, Botian Shi, Yucheng Yang, Youquan Liu, Xingjiao Wu, Qin Chen, Yikang Li, Yu Qiao, et al · 2023
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Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, et al · 2023
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Open-vocabulary point-cloud object detection without 3d annotation
Yuheng Lu, Chenfeng Xu, Xiaobao Wei, Xiaodong Xie, Masayoshi Tomizuka, Kurt Keutzer, and Shanghang Zhang · 2023
Closest in time.