STENet: A hybrid spatio-temporal embedding network for human trajectory forecasting-Reference-Cited by-同舟云学术

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STENet: A hybrid spatio-temporal embedding network for human trajectory forecasting

Published:2021-11 Issue: Volume:106 Page:104487
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Zhang Bo^ORCID,Yuan Chengzhi^ORCID,Wang Tao^ORCID,Liu Hongbo^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference58 articles.

1. Trajectory-based surveillance analysis: A survey;Ahmed;IEEE Trans. Circuits Syst. Video Technol.,2018

2. Social LSTM: Human trajectory prediction in crowded spaces;Alahi,2016

3. Pair-activity analysis from video using qualitative trajectory calculus;AlZoubi;IEEE Trans. Circuits Syst. Video Technol.,2017

4. Social ways: Learning multi-modal distributions of pedestrian trajectories with GANs;Amirian,2019

5. Towards principled methods for training generative adversarial networks;Arjovsky,2017

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Short-term trajectory prediction for individual metro passengers based on multi-level periodicity mining from semantic trajectory;Engineering Applications of Artificial Intelligence;2024-07

2. Under the hood of transformer networks for trajectory forecasting;Pattern Recognition;2023-06

3. Human trajectory forecasting using a flow-based generative model;Engineering Applications of Artificial Intelligence;2022-10

4. Learning to predict diverse trajectory from human motion patterns;Neurocomputing;2022-09

5. REGION: Relevant Entropy Graph spatIO-temporal convolutional Network for Pedestrian Trajectory Prediction;Innovations in Bio-Inspired Computing and Applications;2022

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