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Monocular 3D detection is a challenging task due to the lack of accurate 3D information.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Diederik P Kingma and Jimmy Ba · 2014
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Monocular 3d object detection for autonomous driving
Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2016
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3d object proposals using stereo imagery for accurate object class detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Kosecka · 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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Pyramid stereo matching network
Jia-Ren Chang and Yong-Sheng Chen · 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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Orthographic feature transform for monocular 3d object detection
Thomas Roddick, Alex Kendall, and Roberto Cipolla · 2018
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Leslie N Smith · 2018
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SECOND: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Deep layer aggregation
Fisher Yu, Dequan Wang, Evan Shelhamer, and Trevor Darrell · 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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M3d-rpn: Monocular 3d region proposal network for object detection
Garrick Brazil and Xiaoming Liu · 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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Accurate monocular 3d object detection via color-embedded 3d reconstruction for autonomous driving
Xinzhu Ma, Zhihui Wang, Haojie Li, Pengbo Zhang, Wanli Ouyang, and Xin Fan · 2019
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Roi-10d: Monocular lifting of 2d detection to 6d pose and metric shape
Fabian Manhardt, Wadim Kehl, and Adrien Gaidon · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Pytorch: An imperative style, high-performance deep learning library
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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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Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2019
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Disentangling monocular 3d object detection
Andrea Simonelli, Samuel Rota Bulo, Lorenzo Porzi, Manuel López-Antequera, and Peter Kontschieder · 2019
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger · 2019
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STD: Sparse-to-dense 3D object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2019
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Range conditioned dilated convolutions for scale invariant 3d object detection
Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, and Cristian Sminchisescu · 2020
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Kinematic 3d object detection in monocular video
Garrick Brazil, Gerard Pons-Moll, Xiaoming Liu, and Bernt Schiele · 2020
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Every view counts: Cross-view consistency in 3d object detection with hybrid-cylindrical-spherical voxelization
Qi Chen, Lin Sun, Ernest Cheung, and Alan L Yuille · 2020
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Monopair: Monocular 3d object detection using pairwise spatial relationships
Yongjian Chen, Lei Tai, Kai Sun, and Mingyang Li · 2020
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Learning depth-guided convolutions for monocular 3d object detection
Mingyu Ding, Yuqi Huo, Hongwei Yi, Zhe Wang, Jianping Shi, Zhiwu Lu, and Ping Luo · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Hvpr: Hybrid voxel-point representation for single-stage 3d object detection
Jongyoun Noh, Sanghoon Lee, and Bumsub Ham · 2021
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Is pseudo-lidar needed for monocular 3d object detection?
Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon · 2021
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Categorical depth distribution network for monocular 3d object detection
Cody Reading, Ali Harakeh, Julia Chae, and Steven L Waslander · 2021
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Geometry-based distance decomposition for monocular 3d object detection
Xuepeng Shi, Qi Ye, Xiaozhi Chen, Chuangrong Chen, Zhixiang Chen, and Tae-Kyun Kim · 2021
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Depth-conditioned dynamic message propagation for monocular 3d object detection
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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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Rtm3d: Real-time monocular 3d detection from object keypoints for autonomous driving
Peixuan Li, Huaici Zhao, Pengfei Liu, and Feidao Cao · 2020
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Rethinking pseudo-lidar representation
Xinzhu Ma, Shinan Liu, Zhiyi Xia, Hongwen Zhang, Xingyu Zeng, and Wanli Ouyang · 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
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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
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Point-gnn: Graph neural network for 3d object detection in a point cloud
Weijing Shi and Raj Rajkumar · 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
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Li Wang, Liang Du, Xiaoqing Ye, Yanwei Fu, Guodong Guo, Xiangyang Xue, Jianfeng Feng, and Li Zhang · 2021
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Progressive coordinate transforms for monocular 3d object detection
Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, and Xiangyang Xue · 2021
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Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl · 2021
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Objects are different: Flexible monocular 3d object detection
Yunpeng Zhang, Jiwen Lu, and Jie Zhou · 2021
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Se-ssd: Self-ensembling single-stage object detector from point cloud
Wu Zheng, Weiliang Tang, Li Jiang, and Chi-Wing Fu · 2021
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Monocular 3d object detection: An extrinsic parameter free approach
Yunsong Zhou, Yuan He, Hongzi Zhu, Cheng Wang, Hongyang Li, and Qinhong Jiang · 2021
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Pseudo-stereo for monocular 3d object detection in autonomous driving
Yi-Nan Chen, Hang Dai, and Yong Ding · 2022
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Monodistill: Learning spatial features for monocular 3d object detection
Zhiyu Chong, Xinzhu Ma, Hong Zhang, Yuxin Yue, Haojie Li, Zhihui Wang, and Wanli Ouyang · 2022
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Homography loss for monocular 3d object detection
Jiaqi Gu, Bojian Wu, Lubin Fan, Jianqiang Huang, Shen Cao, Zhiyu Xiang, and Xian-Sheng Hua · 2022
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Monodtr: Monocular 3d object detection with depth-aware transformer
Kuan-Chih Huang, Tsung-Han Wu, Hung-Ting Su, and Winston H Hsu · 2022
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Deviant: Depth equivariant network for monocular 3d object detection
Abhinav Kumar, Garrick Brazil, Enrique Corona, Armin Parchami, and Xiaoming Liu · 2022
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Bevdepth: Acquisition of reliable depth for multi-view 3d object detection
Yinhao Li, Zheng Ge, Guanyi Yu, Jinrong Yang, Zengran Wang, Yukang Shi, Jianjian Sun, and Zeming Li · 2022
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Diversity matters: Fully exploiting depth clues for reliable monocular 3d object detection
Zhuoling Li, Zhan Qu, Yang Zhou, Jianzhuang Liu, Haoqian Wang, and Lihui Jiang · 2022
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Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers
Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Yu Qiao, and Jifeng Dai · 2022
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Monojsg: Joint semantic and geometric cost volume for monocular 3d object detection
Qing Lian, Peiliang Li, and Xiaozhi Chen · 2022
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Petr: Position embedding transformation for multi-view 3d object detection
Yingfei Liu, Tiancai Wang, Xiangyu Zhang, and Jian Sun · 2022
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Did-m3d: Decoupling instance depth for monocular 3d object detection
Liang Peng, Xiaopei Wu, Zheng Yang, Haifeng Liu, and Deng Cai · 2022
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Monocular 3d object detection with depth from motion
Tai Wang, Jiangmiao Pang, and Dahua Lin · 2022
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Transformation-equivariant 3d object detection for autonomous driving
Hai Wu, Chenglu Wen, Wei Li, Xin Li, Ruigang Yang, and Cheng Wang · 2022
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Sparse fuse dense: Towards high quality 3d detection with depth completion
Xiaopei Wu, Liang Peng, Honghui Yang, Liang Xie, Chenxi Huang, Chengqi Deng, Haifeng Liu, and Deng Cai · 2022
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