Fetching the paper…
Reading the bibliography…
In the past few years we have seen great advances in object perception (particularly in 4D space-time dimensions) thanks to deep learning methods.
H. W. Kuhn, “The hungarian method for the assignment problem,”
1955
Earlier work this paper cites.
R. E. Kalman, “A new approach to linear filtering and prediction problems,” 1960
1960
Earlier work this paper cites.
A. Geiger, P. Lenz, and R. Urtasun, “Are we ready for autonomous driving? the kitti vision benchmark suite,” in
2012
Earlier work this paper cites.
D.-H. Lee
2013
Earlier work this paper cites.
A. Milan, S. Roth, and K. Schindler, “Continuous energy minimization for multitarget tracking,” in
2014
Earlier work this paper cites.
O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in
2015
Earlier work this paper cites.
B. Li, T. Zhang, and T. Xia, “Vehicle detection from 3d lidar using fully convolutional network,” in
2016
Earlier work this paper cites.
X. Chen, H. Ma, J. Wan, B. Li, and T. Xia, “Multi-view 3d object detection network for autonomous driving,” in
2017
Earlier work this paper cites.
M. Engelcke, D. Rao, D. Z. Wang, C. H. Tong, and I. Posner, “Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks,” in
2017
Earlier work this paper cites.
B. Li, “3d fully convolutional network for vehicle detection in point cloud,” in
2017
Earlier work this paper cites.
X. Zhu, Y. Wang, J. Dai, L. Yuan, and Y. Wei, “Flow-guided feature aggregation for video object detection,” in
2017
Earlier work this paper cites.
C. Feichtenhofer, A. Pinz, and A. Zisserman, “Detect to track and track to detect,” in
2017
Earlier work this paper cites.
L. Castrejon, K. Kundu, R. Urtasun, and S. Fidler, “Annotating Object Instances with a Polygon-RNN,” in
2017
Earlier work this paper cites.
B. Yang, M. Liang, and R. Urtasun, “Hdnet: Exploiting hd maps for 3d object detection,” in
2018
Earlier work this paper cites.
D. Acuna, H. Ling, A. Kar, and S. Fidler, “Efficient Annotation of Segmentation Datasets with Polygon-RNN++,” in
2018
Earlier work this paper cites.
Y. Zhou and O. Tuzel, “Voxelnet: End-to-end learning for point cloud based 3d object detection,” in
2018
Earlier work this paper cites.
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
2018
Cited alongside, same era.
B. Yang, W. Luo, and R. Urtasun, “Pixor: Real-time 3d object detection from point clouds,” in
2018
Cited alongside, same era.
C. R. Qi, W. Liu, C. Wu, H. Su, and L. J. Guibas, “Frustum pointnets for 3d object detection from rgb-d data,” in
2018
Cited alongside, same era.
S. Wang, Y. Zhou, J. Yan, and Z. Deng, “Fully motion-aware network for video object detection,” in
2018
Cited alongside, same era.
J. Lee, S. Walsh, A. Harakeh, and S. L. Waslander, “Leveraging pre-trained 3d object detection models for fast ground truth generation,” in
2018
Cited alongside, same era.
C. He, H. Zeng, J. Huang, X.-S. Hua, and L. Zhang, “Structure aware single-stage 3d object detection from point cloud,” in
2020
Later among the works it cites.
Z. Yang, Y. Sun, S. Liu, and J. Jia, “3dssd: Point-based 3d single stage object detector,” in
2020
Later among the works it cites.
S. Casas, C. Gulino, S. Suo, K. Luo, R. Liao, and R. Urtasun, “Implicit latent variable model for scene-consistent motion forecasting,” in
2020
Later among the works it cites.
M. Liang, B. Yang, W. Zeng, Y. Chen, R. Hu, S. Casas, and R. Urtasun, “PnPNet: End-to-End Perception and Prediction with Tracking in the Loop,” in
2020
Later among the works it cites.
X. Weng, J. Wang, D. Held, and K. Kitani, “3d multi-object tracking: A baseline and new evaluation metrics,”
2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Casas, W. Luo, and R. Urtasun, “Intentnet: Learning to predict intention from raw sensor data,” in
2018
Cited alongside, same era.
Z. Yang, Y. Sun, S. Liu, X. Shen, and J. Jia, “Std: Sparse-to-dense 3d object detector for point cloud,” in
2019
Cited alongside, same era.
Y. Chai, B. Sapp, M. Bansal, and D. Anguelov, “Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,” in
2019
Cited alongside, same era.
G. P. Meyer, A. Laddha, E. Kee, C. Vallespi-Gonzalez, and C. K. Wellington, “Lasernet: An efficient probabilistic 3d object detector for autonomous driving,” in
2019
Cited alongside, same era.
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom, “Pointpillars: Fast encoders for object detection from point clouds,” in
2019
Cited alongside, same era.
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
2019
Cited alongside, same era.
B. Wang, V. Wu, B. Wu, and K. Keutzer, “Latte: accelerating lidar point cloud annotation via sensor fusion, one-click annotation, and tracking,” in
2019
Cited alongside, same era.
S. Walsh, J. Ku, A. D. Pon, and S. L. Waslander, “Leveraging temporal data for automatic labelling of static vehicles,” in
2020
Later among the works it cites.
H. Caesar, V. Bankiti, A. H. Lang, S. Vora, V. E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom, “nuscenes: A multimodal dataset for autonomous driving,” in
2020
Later among the works it cites.
W. Shi and R. Rajkumar, “Point-gnn: Graph neural network for 3d object detection in a point cloud,” in
2020
Later among the works it cites.
T. Yin, X. Zhou, and P. Krähenbühl, “Center-based 3d object detection and tracking,”
2020
Later among the works it cites.
D. Frossard, S. Suo, S. Casas, J. Tu, R. Hu, and R. Urtasun, “Strobe: Streaming object detection from lidar packets,” in
2020
Later among the works it cites.
Q. Meng, W. Wang, T. Zhou, J. Shen, L. Van Gool, and D. Dai, “Weakly supervised 3d object detection from lidar point cloud,” in
2020
Later among the works it cites.
S. Zakharov, W. Kehl, A. Bhargava, and A. Gaidon, “Autolabeling 3d objects with differentiable rendering of sdf shape priors,” in
2020
Later among the works it cites.
X. Weng, J. Wang, D. Held, and K. Kitani, “3d multi-object tracking: A baseline and new evaluation metrics,” in
2020
Later among the works it cites.
H. Cui, T. Nguyen, F. C. Chou, T. H. Lin, J. Schneider, D. Bradley, and N. Djuric, “Deep kinematic models for kinematically feasible vehicle trajectory predictions,” in
2020
Later among the works it cites.
A. Kuznetsova, H. Rom, N. Alldrin, J. Uijlings, I. Krasin, J. Pont-Tuset, S. Kamali, S. Popov, M. Malloci, A. Kolesnikov,
2020
Later among the works it cites.