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This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).
Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
Martin A. Fischler and Robert C. Bolles · 1987
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2016
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles Ruizhongtai Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2016
Earlier work this paper cites.
Deep sliding shapes for amodal 3d object detection in rgb-d images
S. Song and J. Xiao · 2016
Earlier work this paper cites.
Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee, and Andrew Rabinovich · 2017
Earlier work this paper cites.
3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2017
Earlier work this paper cites.
Submanifold sparse convolutional networks
Benjamin Graham and Laurens van der Maaten · 2017
Earlier work this paper cites.
Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 2017
Cited alongside, same era.
Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Cited alongside, same era.
Frustum pointnets for 3d object detection from RGB-D data
Charles Ruizhongtai Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J. Guibas · 2017
Cited alongside, same era.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J. Guibas · 2017
Cited alongside, same era.
Pointfusion: Deep sensor fusion for 3d bounding box estimation
Pixor: Real-time 3d object detection from point clouds
Bin Yang, Wenjie Luo, and Raquel Urtasun · 2018
Later among the works it cites.
Open3d: A modern library for 3d data processing
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2018
Later among the works it cites.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
Later among the works it cites.
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 · 2019
Closest in time.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Bongsoo Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Danfei Xu, Dragomir Anguelov, and Ashesh Jain · 2017
Cited alongside, same era.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Cited alongside, same era.
Joint 3d proposal generation and object detection from view aggregation
J. Ku, M. Mozifian, J. Lee, A. Harakeh, and S. L. Waslander · 2018
Cited alongside, same era.
Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 2018
Cited alongside, same era.
Multi-task learning as multi-objective optimization
Ozan Sener and Vladlen Koltun · 2018
Cited alongside, same era.
Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
Cited alongside, same era.
https://sgugger.github.io/the-1cycle-policy.html
The 1cycle policy
Cited in the paper.
Closest in time.
Pointpillars: Fast encoders for object detection from point clouds
Alex H. Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Closest in time.
nuScenes 3D Object Detection Challenge, WAD, CVPR 2019
nuTonomy · 2019
Closest in time.
Siyuan Qiao, Huiyu Wang, Chenxi Liu, Wei Shen, and Alan L. Yuille · 2019
Closest in time.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Closest in time.
STD: sparse-to-dense 3d object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2019
Closest in time.