A long-term Trajectory prediction multi-scale AutoRegressive framework (TrajAR), which follows an encoder-decoder structure that progressively refines the predicted trajectory from coarse to fine scales, where coarse-scale predictions establish long-term path backbones and finer scales enhance precision.
Letian Gong, Yan Lin, Xinyue Zhang et al.· Proceedings of the Thirty-Fi...· 0 citations
Low-Rank Prior-Induced Consistency Flow Matching (LOFT) is proposed for efficient and effective distribution modeling under highly sparse data, and introduces an uncertainty-aware rectification mechanism to enable efficient inference by linearizing generative trajectories.
Xiaowei Mao, Tingrui Wu, Yawen Yang et al.· Proceedings of the 32nd ACM...· 0 citations
G-VTM, a generalized vision-trajectory model, is proposed, which captures global map semantics while modeling scenario-and direction-aware interaction based on intuitive visual perception and achieves strong generalized performance under heterogeneous traffic conditions.
Xinyue Zhang, Letian Gong, Yan Lin et al.· Proceedings of the Thirty-Fi...· 0 citations
Low-Rank Prior-Induced Consistency Flow Matching (LOFT) is proposed for efficient and effective distribution modeling under highly sparse data, and introduces an uncertainty-aware rectification mechanism to enable efficient inference by linearizing generative trajectories.
Xiaowei Mao, Tingrui Wu, Yawen Yang et al.· Proceedings of the 32nd ACM...· 0 citations
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