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Many modern robotics systems employ LiDAR as their main sensing modality due to its geometrical richness.
Continuous trajectory estimation for 3d slam from actuated lidar
H. Alismail, L. D. Baker, and B. Browning · 2014
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3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Fast R-CNN
R. Girshick · 2015
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Vehicle detection from 3d lidar using fully convolutional network
B. Li, T. Zhang, and T. Xia · 2016
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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3d fully convolutional network for vehicle detection in point cloud
B. Li · 2017
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Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. Osman Ulusoy, and A. Geiger · 2017
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Low-drift and real-time lidar odometry and mapping
J. Zhang and S. Singh · 2017
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Intentnet: Learning to predict intention from raw sensor data
S. Casas, W. Luo, and R. Urtasun · 2018
Cited alongside, same era.
Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
W. Luo, B. Yang, and R. Urtasun · 2018
Cited alongside, same era.
Pixor: Real-time 3d object detection from point clouds
B. Yang, W. Luo, and R. Urtasun · 2018
Cited alongside, same era.
Pointcnn: Convolution on x-transformed points
Y. Li, R. Bu, M. Sun, W. Wu, X. Di, and B. Chen · 2018
Cited alongside, same era.
Pointwise convolutional neural networks
B.-S. Hua, M.-K. Tran, and S.-K. Yeung · 2018
Cited alongside, same era.
Deep parametric continuous convolutional neural networks
S. Wang, S. Suo, W.-C. Ma, A. Pokrovsky, and R. Urtasun · 2018
Cited alongside, same era.
Lasernet: An efficient probabilistic 3d object detector for autonomous driving
G. P. Meyer, A. Laddha, E. Kee, C. Vallespi-Gonzalez, and C. K. Wellington · 2019
Later among the works it cites.
Deformable filter convolution for point cloud reasoning
Y. Xiong, M. Ren, R. Liao, K. Wong, and R. Urtasun · 2019
Later among the works it cites.
Fast point r-cnn
Y. Chen, S. Liu, X. Shen, and J. Jia · 2019
Later among the works it cites.
Std: Sparse-to-dense 3d object detector for point cloud
Z. Yang, Y. Sun, S. Liu, X. Shen, and J. Jia · 2019
Later among the works it cites.
Pointpillars: Fast encoders for object detection from point clouds
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom · 2019
Later among the works it cites.
PointRCNN: 3d object proposal generation and detection from point cloud
S. Shi, X. Wang, and H. Li · 2019
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Sbnet: Sparse blocks network for fast inference
M. Ren, A. Pokrovsky, B. Yang, and R. Urtasun · 2018
Cited alongside, same era.
Second: Sparsely embedded convolutional detection
Y. Yan, Y. Mao, and B. Li · 2018
Cited alongside, same era.
Hdnet: Exploiting hd maps for 3d object detection
B. Yang, M. Liang, and R. Urtasun · 2018
Cited alongside, same era.
Group normalization
Y. Wu and K. He · 2018
Cited alongside, same era.
Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
S. Shi, C. Guo, L. Jiang, Z. Wang, J. Shi, X. Wang, and H. Li · 2020
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End-to-end multi-view fusion for 3d object detection in lidar point clouds
Y. Zhou, P. Sun, Y. Zhang, D. Anguelov, J. Gao, T. Ouyang, J. Guo, J. Ngiam, and V. Vasudevan · 2020
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Towards streaming image understanding
M. Li, Y.-X. Wang, and D. Ramanan · 2020
Closest in time.
Streaming object detection for 3-d point clouds
W. Han, Z. Zhang, B. Caine, B. Yang, C. Sprunk, O. Alsharif, J. Ngiam, V. Vasudevan, J. Shlens, and Z. Chen · 2020
Closest in time.