BR-GAN: A Pedestrian Trajectory Prediction Model Combined With Behavior Recognition-Reference-Cited by-同舟云学术

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BR-GAN: A Pedestrian Trajectory Prediction Model Combined With Behavior Recognition

Published:2022-12 Issue:12 Volume:23 Page:24609-24620
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Pang Shu Min¹^ORCID,Cao Jin Xin¹^ORCID,Jian Mei Ying²,Lai Jian³,Yan Zhen Ying⁴^ORCID

Affiliation:

1. School of Mathematical Sciences, Inner Mongolia University, Hohhot, China

2. Institute of Transportation Engineering, Inner Mongolia University, Hohhot, China

3. School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, China

4. Inner Mongolia Academy of Science and Technology, Hohhot, China

Funder

National Natural Science Foundation of China

Key Technology Research Plan of Inner Mongolia Autonomous Region

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9972869/09851641.pdf?arnumber=9851641

Reference42 articles.

1. Generative adversarial nets;goodfellow;Proc Adv Neural Inf Process Syst,2014

2. Pedestrian Motion Trajectory Prediction With Stereo-Based 3D Deep Pose Estimation and Trajectory Learning

3. SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction

4. Show, attend and tell: Neural image caption generation with visual attention;xu;Proc Int Conf Mach Learn,2015

5. Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction

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1. SGAMTE-Net: A pedestrian trajectory prediction network based on spatiotemporal graph attention and multimodal trajectory endpoints;Applied Intelligence;2023-12

2. IE-GAN: a data-driven crowd simulation method via generative adversarial networks;Multimedia Tools and Applications;2023-10-20

3. Dynamic resource allocation scheme for mobile edge computing;The Journal of Supercomputing;2023-05-07

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