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Predicting the motion of multiple agents is necessary for planning in dynamic environments.
Trajectory forecasts in unknown environments conditioned on grid-based plans
Nachiket Deo and Mohan M. Trivedi · 2001
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Stanley: The robot that won the darpa grand challenge
Sebastian Thrun, Mike Montemerlo, Hendrik Dahlkamp, David Stavens, Andrei Aron, James Diebel, Philip Fong, John Gale, Morgan Halpenny, Gabriel Hoffmann, et al · 2006
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Junior: The stanford entry in the urban challenge
Michael Montemerlo, Jan Becker, Suhrid Bhat, Hendrik Dahlkamp, Dmitri Dolgov, Scott Ettinger, Dirk Haehnel, Tim Hilden, Gabe Hoffmann, Burkhard Huhnke, et al · 2008
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The DARPA urban challenge: autonomous vehicles in city traffic , volume 56
Martin Buehler, Karl Iagnemma, and Sanjiv Singh · 2009
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You’ll never walk alone: Modeling social behavior for multi-target tracking
Stefano Pellegrini, Andreas Ess, Konrad Schindler, and Luc Van Gool · 2009
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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LambdaNetworks: Modeling long-range interactions without attention
Irwan Bello · 2013
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Trajectory planning for bertha—a local, continuous method
Julius Ziegler, Philipp Bender, Thao Dang, and Christoph Stiller · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Social LSTM: Human trajectory prediction in crowded spaces
Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan, Alexandre Robicquet, Li Fei-Fei, and Silvio Savarese · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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In-datacenter performance analysis of a tensor processing unit
Norman P Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, et al · 2017
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Desire: Distant future prediction in dynamic scenes with interacting agents
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B Choy, Philip HS Torr, and Manmohan Chandraker · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Traphic: Trajectory prediction in dense and heterogeneous traffic using weighted interactions
Rohan Chandra, Uttaran Bhattacharya, Aniket Bera, and Dinesh Manocha · 2018
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Social GAN: Socially acceptable trajectories with generative adversarial networks
Agrim Gupta, Justin Johnson, Li Fei-Fei, Silvio Savarese, and Alexandre Alahi · 2018
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Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
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Attention augmented convolutional networks
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, and Quoc V Le · 2019
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Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2019
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Argoverse: 3d tracking and forecasting with rich maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, et al · 2019
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Multimodal trajectory predictions for autonomous driving using deep convolutional networks
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin, Thi Nguyen, Tzu-Kuo Huang, Jeff Schneider, and Nemanja Djuric · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Axial attention in multidimensional transformers
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, and Tim Salimans · 2019
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Rules of the road: Predicting driving behavior with a convolutional model of semantic interactions
Joey Hong, Benjamin Sapp, and James Philbin · 2019
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Lyft level 5 perception dataset 2020
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
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Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, and Jon Shlens · 2019
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Precog: Prediction conditioned on goals in visual multi-agent settings
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, and Sergey Levine · 2019
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Multi-head attention for joint multi-modal vehicle motion forecasting
Jean Mercat, Thomas Gilles, Nicole Zoghby, Guillaume Sandou, Dominique Beauvois, and Guillermo Gil · 2020
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Learning an uncertainty-aware object detector for autonomous driving
Gregory P. Meyer and Niranjan Thakurdesai · 2020
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Diverse and admissible trajectory forecasting through multimodal context understanding
Seong Hyeon Park, Gyubok Lee, Jimin Seo, Manoj Bhat, Minseok Kang, Jonathan Francis, Ashwin Jadhav, Paul Pu Liang, and Louis-Philippe Morency · 2020
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Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone · 2020
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Axial-deeplab: Stand-alone axial-attention for panoptic segmentation
Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2020
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Multiple futures prediction
Charlie Tang and Russ R Salakhutdinov · 2019
Cited alongside, same era.
Diverse generation for multi-agent sports games
Raymond A Yeh, Alexander G Schwing, Jonathan Huang, and Kevin Murphy · 2019
Cited alongside, same era.
End-to-end interpretable neural motion planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun · 2019
Cited alongside, same era.
Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kümmerle, Hendrik Königshof, Christoph Stiller, Arnaud de La Fortelle, and Masayoshi Tomizuka · 2019
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Multi-agent tensor fusion for contextual trajectory prediction
Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris Baker, Yibiao Zhao, Yizhou Wang, and Ying Nian Wu · 2019
Cited alongside, same era.
Trajformer: Trajectory prediction with local self-attentive contexts for autonomous driving
Manoj Bhat, Jonathan Francis, and Jean Oh · 2020
Cited alongside, same era.
Prank: motion prediction based on ranking
Yuriy Biktairov, Maxim Stebelev, Irina Rudenko, Oleh Shliazhko, and Boris Yangel · 2020
Cited alongside, same era.
Spatio-temporal graph transformer networks for pedestrian trajectory prediction
Cunjun Yu, Xiao Ma, Jiawei Ren, Haiyu Zhao, and Shuai Yi · 2020
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Tnt: Target-driven trajectory prediction
Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2021
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Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles Qi, Yin Zhou, et al · 2021
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HOME: heatmap output for future motion estimation
Thomas Gilles, Stefano Sabatini, Dzmitry Tsishkou, Bogdan Stanciulescu, and Fabien Moutarde · 2021
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Densetnt: End-to-end trajectory prediction from dense goal sets
Junru Gu, Chen Sun, and Hang Zhao · 2021
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Recoat: A deep learning framework with attention mechanism for multi-modal motion prediction
Zhiyu Huang, Xiaoyu Mo, and Chen Lv · 2021
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Rethinking trajectory forecasting evaluation
Boris Ivanovic and Marco Pavone · 2021
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Motioncnn: A strong baseline for motion prediction in autonomous driving
Stepan Konev, Kirill Brodt, and Artsiom Sanakoyeu · 2021
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Multi-modal interactive agent trajectory prediction using heterogeneous edge-enhanced graph attention network
Xiaoyu Mo, Zhiyu Huang, and Chen Lv · 2021
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Toward causal representation learning
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio · 2021
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Bottleneck transformers for visual recognition
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, and Ashish Vaswani · 2021
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Trafficsim: Learning to simulate realistic multi-agent behaviors
Simon Suo, Sebastian Regalado, Sergio Casas, and Raquel Urtasun · 2021
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Identifying driver interactions via conditional behavior prediction
Ekaterina Tolstaya, Reza Mahjourian, Carlton Downey, Balakrishnan Vadarajan, Benjamin Sapp, and Dragomir Anguelov · 2021
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Scaling local self-attention for parameter efficient visual backbones
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake Hechtman, and Jonathon Shlens · 2021
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Waymo open dataset challenge 2021 winners
Waymo · 2021
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Tpcn: Temporal point cloud networks for motion forecasting
Maosheng Ye, Tongyi Cao, and Qifeng Chen · 2021
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Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
Ye Yuan, Xinshuo Weng, Yanglan Ou, and Kris Kitani · 2021
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