ETH

doi:doi:10.57702/vej02xmz

ETH

Pedestrian trajectory forecasting is a fundamental task in multiple utility areas, such as self-driving, autonomous robots, and surveillance systems. The future trajectory forecasting is multi-modal, inﬂuenced by physical interaction with scene contexts and intricate social interactions among pedestrians.

BibTex:

@dataset{Suyi_Chen_and_Hao_Xu_and_Haipeng_Li_and_Kunming_Luo_and_Guanghui_Liu_and_Chi-Wing_Fu_and_Ping_Tan_and_Shuaicheng_Liu_2024,
    abstract = {Pedestrian trajectory forecasting is a fundamental task in multiple utility areas, such as self-driving, autonomous robots, and surveillance systems. The future trajectory forecasting is multi-modal, inﬂuenced by physical interaction with scene contexts and intricate social interactions among pedestrians.},
    author = {Suyi Chen and Hao Xu and Haipeng Li and Kunming Luo and Guanghui Liu and Chi-Wing Fu and Ping Tan and Shuaicheng Liu},
    doi = {10.57702/vej02xmz},
    institution = {No Organization},
    keyword = {'3D Point Cloud Registration', '3D Reconstruction', 'ETH', 'Human Movement', 'Outdoor Scene', 'Pedestrian Trajectory', 'Point Cloud Matching', 'crowded scenes', 'human navigation', 'human trajectory prediction', 'pedestrian trajectory', 'pedestrian trajectory forecasting', 'scene contexts', 'social interactions', 'socially acceptable trajectories', 'trajectory prediction'},
    month = {dec},
    publisher = {TIB},
    title = {ETH},
    url = {https://service.tib.eu/ldmservice/dataset/eth},
    year = {2024}
}