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Accurate and reliable tracking of multiple moving objects in 3D space is an essential component of urban scene understanding.
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2015
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F. Meyer, O. Hlinka, H. Wymeersch, E. Riegler, and F. Hlawatsch, “Distributed localization and tracking of mobile networks including noncooperative objects,” IEEE Transactions on Signal and Information Processing over Networks , vol. 2, no. 1, 2016
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N. Wojke, A. Bewley, and D. Paulus, “Simple online and realtime tracking with a deep association metric,” in Proc. of Intl. Conf. on Image Processing (ICIP) , 2017
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W. Luo, B. Yang, and R. Urtasun, “Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018
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X. Chen, H. Ma, J. Wan, B. Li, and T. Xia, “Multi-view 3d object detection network for autonomous driving,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2017
2017
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F. Meyer, P. Braca, P. Willett, and F. Hlawatsch, “A scalable algorithm for tracking an unknown number of targets using multiple sensors,” IEEE Transactions on Signal Processing , vol. 65, no. 13, 2017
2017
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C. R. Qi, W. Liu, C. Wu, H. Su, and L. J. Guibas, “Frustum pointnets for 3d object detection from rgb-d data,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018
2018
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S. Sharma, J. A. Ansari, J. Krishna Murthy, and K. Madhava Krishna, “Beyond pixels: Leveraging geometry and shape cues for online multi-object tracking,” in Proc. of Intl. Conf. on Robotics and Automation (ICRA) , 2018
2018
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B. Xu and Z. Chen, “Multi-level fusion based 3d object detection from monocular images,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018
2018
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J. Ku, M. Mozifian, J. Lee, A. Harakeh, and S. L. Waslander, “Joint 3d proposal generation and object detection from view aggregation,” in Proc. of Intl. Conf. on Intelligent Robots and Systems (IROS) , 2018
2018
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B. Yang, W. Luo, and R. Urtasun, “Pixor: Real-time 3d object detection from point clouds,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018
2018
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Y. Zhou and O. Tuzel, “Voxelnet: End-to-end learning for point cloud based 3d object detection,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018
2018
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T. Pfeifer and P. Protzel, “Expectation-maximization for adaptive mixture models in graph optimization,” in Proc. of Intl. Conf. on Robotics and Automation (ICRA) , 2019
2019
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J. Ku, A. D. Pon, and S. L. Waslander, “Monocular 3d object detection leveraging accurate proposals and shape reconstruction,” in Proc. of Intl. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2019
2019
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W. Zhang, H. Zhou, S. Sun, Z. Wang, J. Shi, and C. C. Loy, “Robust multi-modality multi-object tracking,” in Proc. of Intl. Conf. on Computer Vision (ICCV) , 2019
2019
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H. Karunasekera, H. Wang, and H. Zhang, “Multiple object tracking with attention to appearance, structure, motion and size,” IEEE Access , vol. 7, 2019
2019
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H.-N. Hu, Q.-Z. Cai, D. Wang, J. Lin, M. Sun, P. Krahenbuhl, T. Darrell, and F. Yu, “Joint monocular 3d vehicle detection and tracking,” in Proc. of Intl. Conf. on Computer Vision (ICCV) , 2019
2019
Later among the works it cites.
K. Burnett, S. Samavi, S. Waslander, T. Barfoot, and A. Schoellig, “autotrack: A lightweight object detection and tracking system for the sae autodrive challenge,” in Proc. of Intl. Conf. on Computer and Robot Vision (CRV) , 2019
2019
Later among the works it cites.
J. Luiten, T. Fischer, and B. Leibe, “Track to reconstruct and reconstruct to track,” IEEE Robotics and Automation Letters , vol. 5, no. 2, 2020
2020
Closest in time.
W. Tian, M. Lauer, and L. Chen, “Online multi-object tracking using joint domain information in traffic scenarios,” IEEE Transactions on Intelligent Transportation Systems , vol. 21, no. 1, 2020
2020
Closest in time.