STI-GAN: Multimodal Pedestrian Trajectory Prediction Using Spatiotemporal Interactions and a Generative Adversarial Network

STI-GAN: Multimodal Pedestrian Trajectory Prediction Using Spatiotemporal Interactions and a Generative Adversarial Network

Predicting the future trajectories of multiple pedestrians in certain scenes has become a key task for ensuring that autonomous vehicles, socially interactive robots and other autonomous mobile platforms can navigate safely. The social interactions between people and the multimodal nature of pedestr...

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Bibliographic Details
Main Authors: Lei Huang, Jihui Zhuang, Xiaoming Cheng, Riming Xu, Hongjie Ma
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Pedestrian trajectory prediction
graph attention mechanism
generative adversarial networks
spatiotemporal
Online Access:https://ieeexplore.ieee.org/document/9387292/

Internet

https://ieeexplore.ieee.org/document/9387292/

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