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Zhuangzhuang Yang, Chengxin Pang and Xinhua Zeng
Predicting the future trajectories of multiple agents is essential for various applications in real life, such as surveillance systems, autonomous driving, and social robots. The trajectory prediction task is influenced by many factors, including individ...
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Di Liu, Qiang Li, Sen Li, Jun Kong and Miao Qi
Pedestrian trajectory prediction is an important task in practical applications such as automatic driving and surveillance systems. It is challenging to effectively model social interactions among pedestrians and capture temporal dependencies. Previous m...
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Liming Lao, Dangkui Du and Pengzhan Chen
This paper proposes a novel prediction model termed the social and spatial attentive generative adversarial network (SSA-GAN). The SSA-GAN framework utilizes a generative approach, where the generator employs social attention mechanisms to accurately mod...
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Hai-Yan Yao, Wang-Gen Wan and Xiang Li
Analysis of pedestrians? motion is important to real-world applications in public scenes. Due to the complex temporal and spatial factors, trajectory prediction is a challenging task. With the development of attention mechanism recently, transformer netw...
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