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In this work, we aim to predict the future motion of vehicles in a traffic scene by explicitly modeling their pairwise interactions.
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Junior: The Stanford entry in the urban challenge
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Autonomous driving in urban environments: Boss and the urban challenge
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Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network
B. Kim, C. M. Kang, J. Kim, S. H. Lee, C. C. Chung, and J. W. Choi · 2017
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G. Xie, H. Gao, L. Qian, B. Huang, K. Li, and J. Wang · 2017
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Relational inductive biases, deep learning, and graph networks
P. Battaglia, J. B. C. Hamrick, V. Bapst, A. Sanchez, V. Zambaldi, M. Malinowski, A. Tacchetti, D. Raposo, A. Santoro, R. Faulkner, C. Gulcehre, F. Song, A. Ballard, J. Gilmer, G. E. Dahl, A. Vaswani, K. Allen, C. Nash, V. J. Langston, C. Dyer, N. Heess, D. Wierstra, P. Kohli, M. Botvinick, O. Vinyals, Y. Li, and R. Pascanu · 2018
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IntentNet: Learning to predict intention from raw sensor data
S. Casas, W. Luo, and R. Urtasun · 2018
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Convolutional social pooling for vehicle trajectory prediction
N. Deo and M. M. Trivedi · 2018
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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
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Red: A simple but effective baseline predictor for the TrajNet benchmark
S. Becker, R. Hug, W. Hübner, and M. Arens · 2019
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Spatially-aware graph neural networks for relational behavior forecasting from sensor data
S. Casas, C. Gulino, R. Liao, and R. Urtasun · 2019
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Multimodal trajectory predictions for autonomous driving using deep convolutional networks
H. Cui, V. Radosavljevic, F.-C. Chou, T.-H. Lin, T. Nguyen, T.-K. Huang, J. Schneider, and N. Djuric · 2019
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Precog: Prediction conditioned on goals in visual multi-agent settings
N. Rhinehart, R. McAllister, K. Kitani, and S. Levine · 2019
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Multi-modal trajectory prediction of surrounding vehicles with maneuver based lstms
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Motion prediction of traffic actors for autonomous driving using deep convolutional networks
N. Djuric, V. Radosavljevic, H. Cui, T. Nguyen, F.-C. Chou, T.-H. Lin, and J. Schneider · 2018
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Neural relational inference for interacting systems
T. Kipf, E. Fetaya, K.-C. Wang, M. Welling, and R. Zemel · 2018
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Predicting the present and future states of multi-agent systems from partially-observed visual data
C. Sun, P. Karlsson, J. Wu, J. B. Tenenbaum, and K. Murphy · 2019
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Relational forward models for multi-agent learning
A. Tacchetti, H. F. Song, P. A. M. Mediano, V. Zambaldi, J. Kramár, N. C. Rabinowitz, T. Graepel, M. Botvinick, and P. W. Battaglia · 2019
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Generating multi-agent trajectories using programmatic weak supervision
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