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Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to date, containing over 1,000 hours of data.
Efficient reductions for imitation learning
S. Ross and D. Bagnell · 2010
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Vision meets robotics: The kitti dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Social lstm: Human trajectory prediction in crowded spaces
A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, and S. Savarese · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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1 year, 1000km: The oxford robotcar dataset
W. Maddern, G. Pascoe, C. Linegar, and P. Newman · 2017
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Desire: Distant future prediction in dynamic scenes with interacting agents
N. Lee, W. Choi, P. Vernaza, C. B. Choy, P. H. S. Torr, and M. K. Chandraker · 2017
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Pointpillars: Fast encoders for object detection from point clouds
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Y. Zhou and O. Tuzel · 2018
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Frustum pointnets for 3d object detection from RGB-D data
C. R. Qi, W. Liu, C. Wu, H. Su, and L. J. Guibas · 2018
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Social gan: Socially acceptable trajectories with generative adversarial networks
A. Gupta, J. Johnson, L. Fei-Fei, S. Savarese, and A. Alahi · 2018
Cited alongside, same era.
Argoverse: 3d tracking and forecasting with rich maps
M. Chang, J. Lambert, P. Sangkloy, J. Singh, S. Bak, A. Hartnett, D. Wang, P. Carr, S. Lucey, D. Ramanan, and J. Hays · 2019
Cited alongside, same era.
Lyft level 5 av dataset 2019
R. Kesten, M. Usman, J. Houston, T. Pandya, K. Nadhamuni, A. Ferreira, M. Yuan, B. Low, A. Jain, P. Ondruska, S. Omari, S. Shah, A. Kulkarni, A. Kazakova, C. Tao, L. Platinsky, W. Jiang, and V. Shet · 2019
Cited alongside, same era.
Multi-task multi-sensor fusion for 3d object detection
M. Liang, B. Yang, Y. Chen, R. Hu, and R. Urtasun · 2019
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
P. Sun, H. Kretzschmar, X. Dotiwalla, A. Chouard, V. Patnaik, P. Tsui, J. Guo, Y. Zhou, Y. Chai, B. Caine, V. Vasudevan, W. Han, J. Ngiam, H. Zhao, A. Timofeev, S. Ettinger, M. Krivokon, A. Gao, A. Joshi, Y. Zhang, J. Shlens, Z. Chen, and D. Anguelov · 2019
Cited alongside, same era.
Multimodal trajectory predictions for autonomous driving using deep convolutional networks
H. Cui, V. Radosavljevic, F. Chou, T. Lin, T. Nguyen, T. Huang, J. Schneider, and N. Djuric · 2019
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Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Y. Chai, B. Sapp, M. Bansal, and D. Anguelov · 2019
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Rules of the road: Predicting driving behavior with a convolutional model of semantic interactions
J. Hong, B. Sapp, and J. Philbin · 2019
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End-to-end interpretable neural motion planner
W. Zeng, W. Luo, S. Suo, A. Sadat, B. Yang, S. Casas, and R. Urtasun · 2019
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
M. Bansal, A. Krizhevsky, and A. Ogale · 2019
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The apolloscape open dataset for autonomous driving and its application
P. Wang, X. Huang, X. Cheng, D. Zhou, Q. Geng, and R. Yang · 2019
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
H. Caesar, V. Bankiti, A. H. Lang, S. Vora, V. E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom · 2019
Cited alongside, same era.
Trafficpredict: Trajectory prediction for heterogeneous traffic-agents
Y. Ma, X. Zhu, S. Zhang, R. Yang, W. Wang, and D. Manocha · 2019
Cited alongside, same era.
S. Casas, C. Gulino, R. Liao, and R. Urtasun · 2020
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Vectornet: Encoding hd maps and agent dynamics from vectorized representation
J. Gao, C. Sun, H. Zhao, Y. Shen, D. Anguelov, C. Li, and C. Schmid · 2020
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Learning to evaluate perception models using planner-centric metrics
J. Philion, A. Kar, and S. Fidler · 2020
Closest in time.