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Predicting the future motion of surrounding agents is essential for autonomous vehicles (AVs) to operate safely in dynamic, human-robot-mixed environments.
Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 1910
Earlier work this paper cites.
Momentum contrast for unsupervised visual representation learning, 2020
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 1911
Earlier work this paper cites.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman and Others · 1960
Earlier work this paper cites.
Vehicle trajectory prediction based on motion model and maneuver recognition
Adam Houenou, Philippe Bonnifait, Véronique Cherfaoui, and Wen Yao · 2013
Earlier work this paper cites.
Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Vehicle trajectory prediction by integrating physics-and maneuver-based approaches using interactive multiple models
Guotao Xie, Hongbo Gao, Lijun Qian, Bin Huang, Keqiang Li, and Jianqiang Wang · 2017
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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
Earlier work this paper cites.
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
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding, 2019
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Earlier work this paper cites.
Social behavior for autonomous vehicles
Wilko Schwarting, Alyssa Pierson, Javier Alonso-Mora, Sertac Karaman, and Daniela Rus · 2019
Earlier work this paper cites.
Speednet: Learning the speediness in videos
Sagie Benaim, Ariel Ephrat, Oran Lang, Inbar Mosseri, William T Freeman, Michael Rubinstein, Michal Irani, and Tali Dekel · 2020
Earlier work this paper cites.
Language models are few-shot learners
Tom B Brown · 2020
Earlier work this paper cites.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Earlier work this paper 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
Earlier work this paper cites.
Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
Earlier work this paper cites.
Learning lane graph representations for motion forecasting
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, and Raquel Urtasun · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
Earlier work this paper cites.
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone · 2020
Earlier work this paper cites.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Earlier work this paper cites.
Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Scene transformer: A unified architecture for predicting multiple agent trajectories
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, et al · 2021
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Socially-compatible behavior design of autonomous vehicles with verification on real human data
Letian Wang, Liting Sun, Masayoshi Tomizuka, and Wei Zhan · 2021
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Tnt: Target-driven trajectory prediction
Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Ben Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, et al · 2021
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Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S Refaat, and Benjamin Sapp · 2023
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Leveraging future relationship reasoning for vehicle trajectory prediction
Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, and Kuk-Jin Yoon · 2023
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Learn tarot with mentor: A meta-learned self-supervised approach for trajectory prediction
Mozhgan Pourkeshavarz, Changhe Chen, and Amir Rasouli · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Attention is all you need, 2023
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2023
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Exploiting map information for self-supervised learning in motion forecasting, 2022
Caio Azevedo, Thomas Gilles, Stefano Sabatini, and Dzmitry Tsishkou · 2022
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Ssl-lanes: Self-supervised learning for motion forecasting in autonomous driving
Prarthana Bhattacharyya, Chengjie Huang, and Krzysztof Czarnecki · 2022
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Masked autoencoders as spatiotemporal learners
Christoph Feichtenhofer, Yanghao Li, Kaiming He, et al · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Efficient game-theoretic planning with prediction heuristic for socially-compliant autonomous driving
Chenran Li, Tu Trinh, Letian Wang, Changliu Liu, Masayoshi Tomizuka, and Wei Zhan · 2022
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi Pang Lam, Dragomir Anguelov, et al · 2022
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Transferable and adaptable driving behavior prediction
Letian Wang, Yeping Hu, Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Changliu Liu · 2022
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Argoverse 2: Next generation datasets for self-driving perception and forecasting
Benjamin Wilson, William Qi, Tanmay Agarwal, John Lambert, Jagjeet Singh, Siddhesh Khandelwal, Bowen Pan, Ratnesh Kumar, Andrew Hartnett, Jhony Kaesemodel Pontes, et al · 2023
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Rmp: A random mask pretrain framework for motion prediction
Yi Yang, Qingwen Zhang, Thomas Gilles, Nazre Batool, and John Folkesson · 2023
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Bootstrap motion forecasting with self-consistent constraints
Maosheng Ye, Jiamiao Xu, Xunnong Xu, Tengfei Wang, Tongyi Cao, and Qifeng Chen · 2023
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Query-centric trajectory prediction
Zikang Zhou, Jianping Wang, Yung-Hui Li, and Yu-Kai Huang · 2023
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Sept: Towards efficient scene representation learning for motion prediction
Zhiqian Lan, Yuxuan Jiang, Yao Mu, Chen Chen, and Shengbo Eben Li · 2024
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Pre-training on synthetic driving data for trajectory prediction
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Learning the latent causal structure for modeling label noise
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Lmdrive: Closed-loop end-to-end driving with large language models
Hao Shao, Yuxuan Hu, Letian Wang, Guanglu Song, Steven L Waslander, Yu Liu, and Hongsheng Li · 2024
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Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2024
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Hpnet: Dynamic trajectory forecasting with historical prediction attention
Xiaolong Tang, Meina Kan, Shiguang Shan, Zhilong Ji, Jinfeng Bai, and Xilin Chen · 2024
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Smartrefine: A scenario-adaptive refinement framework for efficient motion prediction
Yang Zhou, Hao Shao, Letian Wang, Steven L Waslander, Hongsheng Li, and Yu Liu · 2024
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Spatialvla: Exploring spatial representations for visual-language-action model, 2025
Delin Qu, Haoming Song, Qizhi Chen, Yuanqi Yao, Xinyi Ye, Yan Ding, Zhigang Wang, JiaYuan Gu, Bin Zhao, Dong Wang, and Xuelong Li · 2025
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Exploring the potential of encoder-free architectures in 3d lmms, 2025
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