Visual Exposes You: Pedestrian Trajectory Prediction Meets Visual Intention-Reference-Cited by-同舟云学术

Visual Exposes You: Pedestrian Trajectory Prediction Meets Visual Intention

Published:2023-09 Issue:9 Volume:24 Page:9390-9400
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Zhong Xian¹^ORCID,Yan Xu²^ORCID,Yang Zhengwei³^ORCID,Huang Wenxin⁴^ORCID,Jiang Kui⁵^ORCID,Liu Ryan Wen⁶^ORCID,Wang Zheng³^ORCID

Affiliation:

1. Hubei Key Laboratory of Transportation Internet of Things, School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

2. School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

3. School of Computer Science, Wuhan University, Wuhan, China

4. School of Computer Science and Information Engineering, Hubei University, Wuhan, China

5. Huawei Technologies, Cloud BU, Hangzhou, China

6. School of Navigation, Wuhan University of Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Department of Science and Technology, Hubei Provincial People’s Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10235283/10103218.pdf?arnumber=10103218

Reference51 articles.

1. Pedestrian Trajectory Prediction Based on Deep Convolutional LSTM Network

2. SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

3. Social-BiGAT: Multimodal trajectory forecasting using bicycle-GAN and graph attention networks;kosaraju;Proc Adv Neural Inf Process Syst,2019

4. Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction

5. Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

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