Fetching the paper…
Reading the bibliography…
Forecasting the long-term future motion of road actors is a core challenge to the deployment of safe autonomous vehicles (AVs).
Openstreetmap: User-generated street maps
Mordechai Haklay and Patrick Weber · 2008
Earlier work this paper cites.
Multiple choice learning: Learning to produce multiple structured outputs
Abner Guzman-Rivera, Dhruv Batra, and Pushmeet Kohli · 2012
Earlier work this paper cites.
Activity forecasting
Kris M Kitani, Brian D Ziebart, James Andrew Bagnell, and Martial Hebert · 2012
Earlier work this paper cites.
Autonomous vehicle technology: A guide for policymakers
James M Anderson, Kalra Nidhi, Karlyn D Stanley, Paul Sorensen, Constantine Samaras, and Oluwatobi A Oluwatola · 2014
Earlier work this paper cites.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Earlier work this paper cites.
Social lstm: Human trajectory prediction in crowded spaces
Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan, Alexandre Robicquet, Li Fei-Fei, and Silvio Savarese · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Learning social etiquette: Human trajectory understanding in crowded scenes
Alexandre Robicquet, Amir Sadeghian, Alexandre Alahi, and Silvio Savarese · 2016
Earlier work this paper cites.
Generating long-term trajectories using deep hierarchical networks
Stephan Zheng, Yisong Yue, and Jennifer Hobbs · 2016
Earlier work this paper cites.
Economic effects of automated vehicles
Lewis M Clements and Kara M Kockelman · 2017
Earlier work this paper cites.
Autonomous vehicles: Developing a public health research agenda to frame the future of transportation policy
Travis J Crayton and Benjamin Mason Meier · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Autonomous vehicle implementation predictions
Todd Litman · 2017
Earlier work this paper cites.
Policy and society related implications of automated driving: A review of literature and directions for future research
Dimitris Milakis, Bart Van Arem, and Bert Van Wee · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
Cited alongside, same era.
Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2018
Cited alongside, same era.
Relational inductive biases, deep learning, and graph networks
Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, et al · 2018
Cited alongside, same era.
Intentnet: Learning to predict intention from raw sensor data
Sergio Casas, Wenjie Luo, and Raquel Urtasun · 2018
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
Later among the works it cites.
Rules of the road: Predicting driving behavior with a convolutional model of semantic interactions
Joey Hong, Benjamin Sapp, and James Philbin · 2019
Later among the works it cites.
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
Later among the works it cites.
Overcoming limitations of mixture density networks: A sampling and fitting framework for multimodal future prediction
Osama Makansi, Eddy Ilg, Ozgun Cicek, and Thomas Brox · 2019
Later among the works it cites.
Multi-head attention for multi-modal joint vehicle motion forecasting, 2019
Jean Mercat, Thomas Gilles, Nicole El Zoghby, Guillaume Sandou, Dominique Beauvois, and Guillermo Pita Gil · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
How would surround vehicles move? a unified framework for maneuver classification and motion prediction
Nachiket Deo, Akshay Rangesh, and Mohan M Trivedi · 2018
Cited alongside, same era.
Multi-modal trajectory prediction of surrounding vehicles with maneuver based lstms
Nachiket Deo and Mohan M Trivedi · 2018
Cited alongside, same era.
Motion prediction of traffic actors for autonomous driving using deep convolutional networks
Nemanja Djuric, Vladan Radosavljevic, Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, and Jeff Schneider · 2018
Cited alongside, same era.
Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
Wenjie Luo, Bin Yang, and Raquel Urtasun · 2018
Cited alongside, same era.
R2p2: A reparameterized pushforward policy for diverse, precise generative path forecasting
Nicholas Rhinehart, Kris M Kitani, and Paul Vernaza · 2018
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2019
Cited alongside, same era.
Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2019
Cited alongside, same era.
Covernet: Multimodal behavior prediction using trajectory sets
Tung Phan-Minh, Elena Corina Grigore, Freddy A Boulton, Oscar Beijbom, and Eric M Wolff · 2019
Later among the works it cites.
Precog: Prediction conditioned on goals in visual multi-agent settings
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, and Sergey Levine · 2019
Later among the works it cites.
Sophie: An attentive gan for predicting paths compliant to social and physical constraints
Amir Sadeghian, Vineet Kosaraju, Ali Sadeghian, Noriaki Hirose, Hamid Rezatofighi, and Silvio Savarese · 2019
Later among the works it cites.
Scalability in perception for autonomous driving: An open dataset benchmark
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2019
Later among the works it cites.
Multiple futures prediction
Charlie Tang and Russ R Salakhutdinov · 2019
Later among the works it cites.
A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and Philip S Yu · 2019
Later among the works it cites.
Vectornet: Encoding hd maps and agent dynamics from vectorized representation
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, and Cordelia Schmid · 2020
Closest in time.
Learning lane graph representations for motion forecasting
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, and Raquel Urtasun · 2020
Closest in time.
Trajectron++: Multi-agent generative trajectory forecasting with heterogeneous data for control
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone · 2020
Closest in time.