SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction

doi:doi:10.57702/9fmbom5m

SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction

Pedestrian trajectory prediction is an important technique of autonomous driving, which has become a research hot-spot in recent years. In order to accurately predict the reasonable future trajectory of pedestrians, it is inevitable to consider social interactions among pedestrians and the influence of surrounding scene simultaneously.

BibTex:

@dataset{Pei_Lv_and_Wentong_Wang_and_Yunxin_Wang_and_Yuzhen_Zhang_and_Mingliang_Xu_and_Changsheng_Xu_2024,
    abstract = {Pedestrian trajectory prediction is an important technique of autonomous driving, which has become a research hot-spot in recent years. In order to accurately predict the reasonable future trajectory of pedestrians, it is inevitable to consider social interactions among pedestrians and the influence of surrounding scene simultaneously.},
    author = {Pei Lv and Wentong Wang and Yunxin Wang and Yuzhen Zhang and Mingliang Xu and Changsheng Xu},
    doi = {10.57702/9fmbom5m},
    institution = {No Organization},
    keyword = {'Graph Convolutional Network', 'Pedestrian Trajectory Prediction', 'Social Attention'},
    month = {dec},
    publisher = {TIB},
    title = {SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction},
    url = {https://service.tib.eu/ldmservice/dataset/ssagcn--social-soft-attention-graph-convolution-network-for-pedestrian-trajectory-prediction},
    year = {2024}
}