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Predicting human behavior is a difficult and crucial task required for motion planning.
Social force model for pedestrian dynamics
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Probabilistic Robotics
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Pattern recognition and machine learning
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You’ll never walk alone: Modeling social behavior for multi-target tracking
S. Pellegrini, A. Ess, K. Schindler, and L. van Gool · 2009
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Who are you with and where are you going?
K. Yamaguchi, A. C. Berg, L. E. Ortiz, and T. L. Berg · 2011
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Activity forecasting
K. M. Kitani, B. D. Ziebart, J. A. Bagnell, and M. Hebert · 2012
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Articulated human detection with flexible mixtures of parts
Y. Yang and D. Ramanan · 2012
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Scalable object detection using deep neural networks
D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov · 2014
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SSD: Single shot MultiBbox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 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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SocialLSTM: 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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Forecasting social navigation in crowded complex scenes
A. Robicquet, A. Alahi, A. Sadeghian, B. Anenberg, J. Doherty, E. Wu, and S. Savarese · 2016
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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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What uncertainties do we need in Bayesian deep learning for computer vision?
A. Kendall and Y. Gal · 2017
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Forecasting interactive dynamics of pedestrians with fictitious play
W.-C. Ma, D.-A. Huang, N. Lee, and K. M. Kitani · 2017
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Car-net: Clairvoyant attentive recurrent network
A. Sadeghian, F. Legros, M. Voisin, R. Vesel, A. Alahi, and S. Savarese · 2018
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Generative modeling of multimodal multi-human behavior
B. Ivanovic, E. Schmerling, K. Leung, and M. Pavone · 2018
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Accurate and diverse sampling of sequences based on a “best of many” sample objective
A. Bhattacharyya, B. Schiele, and M. Fritz · 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
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RED: A simple but effective baseline predictor for the TrajNet benchmark
S. Becker, R. Hug, W. Hubner, and M. Arens · 2018
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Rules of the Road: Predicting driving behavior with a convolutional model of semantic interactions
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N. Rhinehart and K. M. Kitani · 2017
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Carla: An open urban driving simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
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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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IntentNet: Learning to predict intention from raw sensor data
S. Casas, W. Luo, and R. Urtasun · 2018
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R2P2: A reparameterized pushforward policy for diverse, precise generative path forecasting
N. Rhinehart, K. M. Kitani, and P. Vernaza · 2018
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J. Hong, B. Sapp, and J. Philbin · 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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PRECOG: Prediction conditioned on goals in visual multi-agent settings
N. Rhinehart, R. McAllister, K. Kitani, and S. Levine · 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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