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3D object detection is a fundamental and challenging task for 3D scene understanding, and the monocular-based methods can serve as an economical alternative to the stereo-based or LiDAR-based methods.
Are we ready for autonomous driving? the KITTI vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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3d object proposals for accurate object class detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G. Berneshawi, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2015
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Cross modal distillation for supervision transfer
Saurabh Gupta, Judy Hoffman, and Jitendra Malik · 2016
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Learning efficient object detection models with knowledge distillation
Guobin Chen, Wongun Choi, Xiang Yu, Tony X. Han, and Manmohan Chandraker · 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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Fisher Yu, Dequan Wang, and Trevor Darrell · 2017
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Pyramid stereo matching network
Jia-Ren Chang and Yong-Sheng Chen · 2018
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Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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In defense of classical image processing: Fast depth completion on the cpu
Jason Ku, Ali Harakeh, and Steven L Waslander · 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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Multi-level fusion based 3d object detection from monocular images
Bin Xu and Zhenzhong Chen · 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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Structured knowledge distillation for semantic segmentation
Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, and Jingdong Wang · 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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Monogrnet: A geometric reasoning network for monocular 3d object localization
Zengyi Qin, Jinglu Wang, and Yan Lu · 2019
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Orthographic feature transform for monocular 3d object detection
Thomas Roddick, Alex Kendall, and Roberto Cipolla · 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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Disentangling monocular 3d object detection
Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Manuel Lopez-Antequera, and Peter Kontschieder · 2019
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FCOS: fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
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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Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving
Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, and Kilian Q. Weinberger · 2020
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Neighbor-vote: Improving monocular 3d object detection through neighbor distance voting
Xiaomeng Chu, Jiajun Deng, Yao Li, Zhenxun Yuan, Yanyong Zhang, Jianmin Ji, and Yu Zhang · 2021
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General instance distillation for object detection
Xing Dai, Zeren Jiang, Zhao Wu, Yiping Bao, Zhicheng Wang, Si Liu, and Erjin Zhou · 2021
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Liga-stereo: Learning lidar geometry aware representations for stereo-based 3d detector
Xiaoyang Guo, Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2021
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Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, and Kilian Q. Weinberger · 2019
Cited alongside, same era.
Monocular 3d object detection with pseudo-lidar point cloud
Xinshuo Weng and Kris Kitani · 2019
Cited alongside, same era.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Monocular 3d object detection with decoupled structured polygon estimation and height-guided depth estimation
Yingjie Cai, Buyu Li, Zeyu Jiao, Hongsheng Li, Xingyu Zeng, and Xiaogang Wang · 2020
Cited alongside, same era.
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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Inter-region affinity distillation for road marking segmentation
Yuenan Hou, Zheng Ma, Chunxiao Liu, Tak-Wai Hui, and Chen Change Loy · 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
Cited alongside, same era.
Groomed-nms: Grouped mathematically differentiable nms for monocular 3d object detection
Abhinav Kumar, Garrick Brazil, and Xiaoming Liu · 2021
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Autoshape: Real-time shape-aware monocular 3d object detection
Zongdai Liu, Dingfu Zhou, Feixiang Lu, Jin Fang, and Liangjun Zhang · 2021
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Geometry uncertainty projection network for monocular 3d object detection
Yan Lu, Xinzhu Ma, Lei Yang, Tianzhu Zhang, Yating Liu, Qi Chu, Junjie Yan, and Wanli Ouyang · 2021
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M3dssd: Monocular 3d single stage object detector
Shujie Luo, Hang Dai, Ling Shao, and Yong Ding · 2021
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Delving into localization errors for monocular 3d object detection
Xinzhu Ma, Yinmin Zhang, Dan Xu, Dongzhan Zhou, Shuai Yi, Haojie Li, and Wanli Ouyang · 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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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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