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Due to the inherent ill-posed nature of 2D-3D projection, monocular 3D object detection lacks accurate depth recovery ability.
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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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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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollar, and Ross Girshick · 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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Pyramid stereo matching network
Jia-Ren Chang and Yong-Sheng Chen · 2018
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Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2018
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao Yao, Zixin Luo, Shiwei Li, Tian Fang, and Long Quan · 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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Point-based multi-view stereo network
Rui Chen, Songfang Han, Jing Xu, and Hao Su · 2019
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Group-wise correlation stereo network
Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, and Hongsheng Li · 2019
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Stereo r-cnn based 3d object detection for autonomous driving
Peiliang Li, Xiaozhi Chen, and Shaojie Shen · 2019
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Multi-sensor 3d object box refinement for autonomous driving
Peiliang Li, Siqi Liu, and Shaojie Shen · 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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Disentangling monocular 3d object detection
Andrea Simonelli, Samuel Rota Rota Bulò, 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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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 Campbell, and Kilian Q Weinberger · 2019
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Monorun: Monocular 3d object detection by reconstruction and uncertainty propagation
Hansheng Chen, Yuyao Huang, Wei Tian, Zhong Gao, and Lu Xiong · 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
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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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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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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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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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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Reinforced axial refinement network for monocular 3d object detection
Lijie Liu, Chufan Wu, Jiwen Lu, Lingxi Xie, Jie Zhou, and Qi Tian · 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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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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Are we missing confidence in pseudo-lidar methods for monocular 3d object detection?
Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder, and Elisa Ricci · 2021
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Depth-conditioned dynamic message propagation for monocular 3d object detection
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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Objects are different: Flexible monocular 3d object detection
Yunpeng Zhang, Jiwen Lu, and Jie Zhou · 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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The devil is in the task: Exploiting reciprocal appearance-localization features for monocular 3d object detection
Zhikang Zou, Xiaoqing Ye, Liang Du, Xianhui Cheng, Xiao Tan, Li Zhang, Jianfeng Feng, Xiangyang Xue, and Errui Ding · 2021
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