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Human trajectory forecasting is a critical challenge in fields such as robotics and autonomous driving.
“Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior.,”
Judith A Ouellette and Wendy Wood, · 1998
Earlier work this paper cites.
“Crowds by example,”
Alon Lerner, Yiorgos Chrysanthou, and Dani Lischinski, · 2007
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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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“Towards fully autonomous driving: Systems and algorithms,”
Jesse Levinson, Jake Askeland, Jan Becker, Jennifer Dolson, David Held, Soeren Kammel, J Zico Kolter, Dirk Langer, Oliver Pink, Vaughan Pratt, et al., · 2011
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.
“Ask me anything: Dynamic memory networks for natural language processing,”
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, and Richard Socher, · 2016
Earlier work this paper cites.
“Analysis of recurrent neural networks for probabilistic modeling of driver behavior,”
Jeremy Morton, Tim A Wheeler, and Mykel J Kochenderfer, · 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
Cited alongside, same era.
“Social gan: Socially acceptable trajectories with generative adversarial networks,”
Agrim Gupta, Justin Johnson, Li Fei-Fei, Silvio Savarese, and Alexandre Alahi, · 2018
Cited alongside, same era.
“Ss-lstm: A hierarchical lstm model for pedestrian trajectory prediction,”
Hao Xue, Du Q Huynh, and Mark Reynolds, · 2018
Cited alongside, same era.
“Stgat: Modeling spatial-temporal interactions for human trajectory prediction,”
Yingfan Huang, Huikun Bi, Zhaoxin Li, Tianlu Mao, and Zhaoqi Wang, · 2019
Cited alongside, same era.
“Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data,”
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone, · 2020
Cited alongside, same era.
“Continual multi-agent interaction behavior prediction with conditional generative memory,”
Hengbo Ma, Yaofeng Sun, Jiachen Li, Masayoshi Tomizuka, and Chiho Choi, · 2021
Later among the works it cites.
“Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning,”
Chenxin Xu, Maosen Li, Zhenyang Ni, Ya Zhang, and Siheng Chen, · 2022
Later among the works it cites.
“Stochastic trajectory prediction via motion indeterminacy diffusion,”
Tianpei Gu, Guangyi Chen, Junlong Li, Chunze Lin, Yongming Rao, Jie Zhou, and Jiwen Lu, · 2022
Later among the works it cites.
“Forecasting human trajectory from scene history,”
Mancheng Meng, Ziyan Wu, Terrence Chen, Xiran Cai, Xiang Zhou, Fan Yang, and Dinggang Shen, · 2022
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“Remember intentions: retrospective-memory-based trajectory prediction,”
Chenxin Xu, Weibo Mao, Wenjun Zhang, and Siheng Chen, · 2022
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“It is not the journey but the destination: Endpoint conditioned trajectory prediction,”
Karttikeya Mangalam, Harshayu Girase, Shreyas Agarwal, Kuan-Hui Lee, Ehsan Adeli, Jitendra Malik, and Adrien Gaidon, · 2020
Cited alongside, same era.
“Mantra: Memory augmented networks for multiple trajectory prediction,”
Francesco Marchetti, Federico Becattini, Lorenzo Seidenari, and Alberto Del Bimbo, · 2020
Cited alongside, same era.
“Social-implicit: Rethinking trajectory prediction evaluation and the effectiveness of implicit maximum likelihood estimation,”
Abduallah Mohamed, Deyao Zhu, Warren Vu, Mohamed Elhoseiny, and Christian Claudel, · 2022
Later among the works it cites.
“Temporal pyramid network for pedestrian trajectory prediction with multi-supervision,”
Rongqin Liang, Yuanman Li, Xia Li, Yi Tang, Jiantao Zhou, and Wenbin Zou, · 2037
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