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Learning socially-aware motion representations is at the core of recent advances in multi-agent problems, such as human motion forecasting and robot navigation in crowds.
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
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Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold, Daniel Mankowitz, and Todd Hester · 1904
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Causal Confusion in Imitation Learning
Pim de Haan, Dinesh Jayaraman, and Sergey Levine · 1905
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Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
Ruohan Wang, Carlo Ciliberto, Pierluigi Amadori, and Yiannis Demiris · 1905
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Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling
Yuping Luo, Huazhe Xu, and Tengyu Ma · 1907
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DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning
Chiho Choi, Srikanth Malla, Abhishek Patil, and Joon Hee Choi · 1908
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Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 1911
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Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen · 1938
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Efficient Reductions for Imitation Learning
Stephane Ross and Drew Bagnell · 1938
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A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stephane Ross, Geoffrey Gordon, and Drew Bagnell · 1938
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ALVINN: An Autonomous Land Vehicle in a Neural Network
Dean A. Pomerleau · 1989
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Social Force Model for Pedestrian Dynamics
Dirk Helbing and Peter Molnar · 1998
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Algorithms for Inverse Reinforcement Learning
Andrew Y. Ng and Stuart Russell · 2000
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A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2002
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EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning
Jiachen Li, Fan Yang, Masayoshi Tomizuka, and Chiho Choi · 2003
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Apprenticeship Learning via Inverse Reinforcement Learning
Pieter Abbeel and Andrew Y. Ng · 2004
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Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2005
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Dimensionality Reduction by Learning an Invariant Mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Ching-Yao Chuang, Joshua Robinson, Lin Yen-Chen, Antonio Torralba, and Stefanie Jegelka · 2007
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Crowds by Example
Alon Lerner, Yiorgos Chrysanthou, and Dani Lischinski · 2007
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Contrastive Learning for Unpaired Image-to-Image Translation
Taesung Park, Alexei A. Efros, Richard Zhang, and Jun-Yan Zhu · 2007
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Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
Senthil Purushwalkam and Abhinav Gupta · 2007
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Multi-label Contrastive Predictive Coding
Jiaming Song and Stefano Ermon · 2007
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End-to-end Contextual Perception and Prediction with Interaction Transformer
Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, and Raquel Urtasun · 2008
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DSDNet: Deep Structured self-Driving Network
Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, and Raquel Urtasun · 2008
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Maximum entropy inverse reinforcement learning
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey · 2008
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Search-based structured prediction
Hal Daumé, John Langford, and Daniel Marcu · 2009
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Abnormal crowd behavior detection using social force model
Ramin Mehran, Alexis Oyama, and Mubarak Shah · 2009
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Hard Negative Mixing for Contrastive Learning
Yannis Kalantidis, Mert Bulent Sariyildiz, Noe Pion, Philippe Weinzaepfel, and Diane Larlus · 2010
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People tracking with human motion predictions from social forces
Matthias Luber, Johannes A. Stork, Gian Diego Tipaldi, and Kai O Arras · 2010
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Improving Data Association by Joint Modeling of Pedestrian Trajectories and Groupings
Stefano Pellegrini, Andreas Ess, and Luc Van Gool · 2010
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Contrastive Learning with Hard Negative Samples
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, and Stefanie Jegelka · 2010
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Unfreezing the robot: Navigation in dense, interacting crowds
Peter Trautman and Andreas Krause · 2010
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Reciprocal n-Body Collision Avoidance
Jur van den Berg, Stephen J. Guy, Ming Lin, and Dinesh Manocha · 2011
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Social force model with explicit collision prediction
Francesco Zanlungo, Tetsushi Ikeda, and Takayuki Kanda · 2011
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Batch Reinforcement Learning
Sascha Lange, Thomas Gabel, and Martin Riedmiller · 2012
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Representation Learning: A Review and New Perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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Robot companion: A social-force based approach with human awareness-navigation in crowded environments
Gonzalo Ferrer, Anais Garrell, and Alberto Sanfeliu · 2013
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Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Deep Contextualized Word Representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer · 2018
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A Literature Review on the Prediction of Pedestrian Behavior in Urban Scenarios
Daniela Ridel, Eike Rehder, Martin Lauer, Christoph Stiller, and Denis Wolf · 2018
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Time-Contrastive Networks: Self-Supervised Learning from Video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, and Sergey Levine · 2018
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3DOF Pedestrian Trajectory Prediction Learned from Long-Term Autonomous Mobile Robot Deployment Data
L. Sun, Z. Yan, S. M. Mellado, M. Hanheide, and T. Duckett · 2018
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Unsupervised Feature Learning via Non-parametric Instance Discrimination
Zhirong Wu, Yuanjun Xiong, Stella Yu, and Dahua Lin · 2018
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Socially-Aware Large-Scale Crowd Forecasting
Alexandre Alahi, Vignesh Ramanathan, and Li Fei-Fei · 2014
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Notes on Noise Contrastive Estimation and Negative Sampling
Chris Dyer · 2014
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word2vec Explained: deriving Mikolov et al.’s negative-sampling word-embedding method
Yoav Goldberg and Omer Levy · 2014
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba · 2014
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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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Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories With GANs
Javad Amirian, Jean-Bernard Hayet, and Julien Pettre · 2019
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Disagreement-Regularized Imitation Learning
Kiante Brantley, Wen Sun, and Mikael Henaff · 2019
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Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning
Changan Chen, Yuejiang Liu, Sven Kreiss, and Alexandre Alahi · 2019
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Exploring the Limitations of Behavior Cloning for Autonomous Driving
Felipe Codevilla, Eder Santana, Antonio M. Lopez, and Adrien Gaidon · 2019
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Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto, David Meger, and Doina Precup · 2019
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STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction
Yingfan Huang, Huikun Bi, Zhaoxin Li, Tianlu Mao, and Zhaoqi Wang · 2019
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The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
Boris Ivanovic and Marco Pavone · 2019
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Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks
Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian Reid, Hamid Rezatofighi, and Silvio Savarese · 2019
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Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, and Sergey Levine · 2019
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Improving Movement Prediction of Traffic Actors using Off-road Loss and Bias Mitigation, 2019
M. Niedoba, Henggang Cui, K. Luo, Darshan Hegde, Fang-Chieh Chou, and Nemanja Djuric · 2019
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Representation Learning with Contrastive Predictive Coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2019
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SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards
Siddharth Reddy, Anca D. Dragan, and Sergey Levine · 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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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
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An Optimistic Perspective on Offline Reinforcement Learning
Rishabh Agarwal, Dale Schuurmans, and Mohammad Norouzi · 2020
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MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2020
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Space-Time Correspondence as a Contrastive Random Walk
Allan Jabri, Andrew Owens, and Alexei Efros · 2020
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Collaborative Sampling in Generative Adversarial Networks
Yuejiang Liu, Parth Kothari, and Alexandre Alahi · 2020
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Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
A. Mohamed, K. Qian, M. Elhoseiny, and C. Claudel · 2020
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Human motion trajectory prediction: a survey
Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M Kitani, Dariu M Gavrila, and Kai O Arras · 2020
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Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data
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Multi-Agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning
Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton de Ruiter, and Jonathan P. How · 2020
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Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, and Stefano Ermon · 2020
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Recursive Social Behavior Graph for Trajectory Prediction
Jianhua Sun, Qinhong Jiang, and Cewu Lu · 2020
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Injecting knowledge in data-driven vehicle trajectory predictors
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Exploring Simple Siamese Representation Learning
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Human trajectory forecasting: A deep learning perspective
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Interpretable social anchors for human trajectory forecasting in crowds
Parth Kothari, Brian Sifringer, and Alexandre Alahi · 2021
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