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In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories.
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Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, et al · 2019
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Tnt: Target-driven trajectory prediction
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nuscenes: A multimodal dataset for autonomous driving
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End-to-end contextual perception and prediction with interaction transformer
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Covernet: Multimodal behavior prediction using trajectory sets
Tung Phan-Minh, Elena Corina Grigore, Freddy A Boulton, Oscar Beijbom, and Eric M Wolff · 2020
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Lapred: Lane-aware prediction of multi-modal future trajectories of dynamic agents
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Air 2 for interaction prediction
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Interpret: Interaction-dataset-based prediction challenge
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