Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
Oct 1, 2024
This paper presents a novel trajectory prediction method using masked autoencoders and actor-specific token memory to improve accuracy and efficiency under distribution shifts.
Jun 17, 2024
This paper introduces an interaction-aware, trajectory-conditioned model for long-term multi-agent human pose forecasting, featuring a novel graph-based interaction module and validated with a new, extensive dataset.
Jun 17, 2024
This paper proposes a method using Neural Stochastic Differential Equations to improve cross-dataset transferability in multi-agent trajectory prediction by addressing discrepancies in data acquisition strategies.
Mar 24, 2024
This paper presents a novel vehicle trajectory prediction approach using lane information and probabilistic modeling to predict future agent interactions, achieving state-of-the-art performance on long-term prediction benchmarks.
May 24, 2023
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Oct 21, 2022
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
Oct 11, 2021
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
Dec 29, 2020