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Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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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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Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov · 2012
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Fast r-cnn
Ross Girshick · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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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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Voting for voting in online point cloud object detection
Dominic Zeng Wang and Ingmar Posner · 2015
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Simple online and realtime tracking
Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, and Ben Upcroft · 2016
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Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
Martin Engelcke, Dushyant Rao, Dominic Zeng Wang, Chi Hay Tong, and Ingmar Posner · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar · 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 Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Simple online and realtime tracking with a deep association metric
Nicolai Wojke, Alex Bewley, and Dietrich Paulus · 2017
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
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The 1cycle policy
Sylvain Gugger · 2018
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Acquisition of localization confidence for accurate object detection
Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, and Yuning Jiang · 2018
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Cornernet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 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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Complex-yolo: An euler-region-proposal for real-time 3d object detection on point clouds
Martin Simony, Stefan Milzy, Karl Amendey, and Horst-Michael Gross · 2018
Cited alongside, same era.
Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
Cited alongside, same era.
Pixor: Real-time 3d object detection from point clouds
Bin Yang, Wenjie Luo, and Raquel Urtasun · 2018
Cited alongside, same era.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
Cited alongside, same era.
Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2019
Cited alongside, same era.
Tracking without bells and whistles
Philipp Bergmann, Tim Meinhardt, and Laura Leal-Taixe · 2019
Cited alongside, same era.
Class-balanced grouping and sampling for point cloud 3d object detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, and Gang Yu · 2019
Later among the works it cites.
Range conditioned dilated convolutions for scale invariant 3d object detection
Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, and Cristian Sminchisescu · 2020
Closest in time.
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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Every view counts: Cross-view consistency in 3d object detection with hybrid-cylindrical-spherical voxelization
Qi Chen, Lin Sun, Ernest Cheung, Kui Jia, and Alan Yuille · 2020
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Object as hotspots: An anchor-free 3d object detection approach via firing of hotspots
Qi Chen, Lin Sun, Zhixin Wang, Kui Jia, and Alan Yuille · 2020
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Fast point r-cnn
Yilun Chen, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2019
Cited alongside, same era.
Multiple object tracking with attention to appearance, structure, motion and size
H. Karunasekera, H. Wang, and H. Zhang · 2019
Cited alongside, same era.
Pointpillars: Fast encoders for object detection from point clouds
Alex H. Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Cited alongside, same era.
Gs3d: An efficient 3d object detection framework for autonomous driving
Buyu Li, Wanli Ouyang, Lu Sheng, Xingyu Zeng, and Xiaogang Wang · 2019
Cited alongside, same era.
Multi-task multi-sensor fusion for 3d object detection
Ming Liang, Bin Yang, Yun Chen, Rui Hu, and Raquel Urtasun · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Closest in time.
Probabilistic 3d multi-object tracking for autonomous driving
Hsu-kuang Chiu, Antonio Prioletti, Jie Li, and Jeannette Bohg · 2020
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Afdet: Anchor free one stage 3d object detection
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu, Yu Wang, Sijia Chen, Li Huang, and Yuan Li · 2020
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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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What you see is what you get: Exploiting visibility for 3d object detection
Peiyun Hu, Jason Ziglar, David Held, and Deva Ramanan · 2020
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An lstm approach to temporal 3d object detection in lidar point clouds
Rui Huang, Wanyue Zhang, Abhijit Kundu, Caroline Pantofaru, David A Ross, Thomas Funkhouser, and Alireza Fathi · 2020
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Dops: Learning to detect 3d objects and predict their 3d shapes
Mahyar Najibi, Guangda Lai, Abhijit Kundu, Zhichao Lu, Vivek Rathod, Thomas Funkhouser, Caroline Pantofaru, David Ross, Larry S Davis, and Alireza Fathi · 2020
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Learning to evaluate perception models using planner-centric metrics
Jonah Philion, Amlan Kar, and Sanja Fidler · 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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From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network
Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2020
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Scalability in perception for autonomous driving: An open dataset benchmark
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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Pointpainting: Sequential fusion for 3d object detection
Sourabh Vora, Alex H Lang, Bassam Helou, and Oscar Beijbom · 2020
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Pillar-based object detection for autonomous driving
Yue Wang, Alireza Fathi, Abhijit Kundu, David Ross, Caroline Pantofaru, Tom Funkhouser, and Justin Solomon · 2020
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A Baseline for 3D Multi-Object Tracking
Xinshuo Weng and Kris Kitani · 2020
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3dssd: Point-based 3d single stage object detector
Zetong Yang, Yanan Sun, Shu Liu, and Jiaya Jia · 2020
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Lidar-based online 3d video object detection with graph-based message passing and spatiotemporal transformer attention
Junbo Yin, Jianbing Shen, Chenye Guan, Dingfu Zhou, and Ruigang Yang · 2020
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Tracking objects as points
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Ssn: Shape signature networks for multi-class object detection from point clouds
Xinge Zhu, Yuexin Ma, Tai Wang, Yan Xu, Jianping Shi, and Dahua Lin · 2020
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