STGlow: A Flow-Based Generative Framework With Dual-Graphormer for Pedestrian Trajectory Prediction

Rongqin Liang; Yuanman Li; Jiantao Zhou; Xia Li

doi:10.1109/tnnls.2023.3294998

journal article Nov 01, 2024

STGlow: A Flow-Based Generative Framework With Dual-Graphormer for Pedestrian Trajectory Prediction

Rongqin Liang

Yuanman Li

Jiantao Zhou

Xia Li

IEEE Transactions on Neural Networks and Learning Systems Vol. 35 No. 11 pp. 16504-16517 · Institute of Electrical and Electronics Engineers (IEEE)

View at Publisher Save 10.1109/tnnls.2023.3294998

Topics

No keywords indexed for this article. Browse by subject →

References

73

[1]

10.1109/cvpr.2019.00587

[2]

10.1109/tim.2005.858824

[3]

10.3390/s100908028

[4]

10.1109/tnnls.2022.3159538

[5]

10.1109/tip.2016.2540813

[6]

10.1109/tip.2012.2211373

[7]

10.1109/tip.2008.2012070

[8]

10.1109/cvpr.2018.00240

[9]

10.1109/cvpr42600.2020.01443

[10]

10.1007/978-3-030-58610-2_30

[11]

10.1609/aaai.v35i3.16299

[12]

10.1109/iccv48922.2021.00967

[13]

10.1109/tnse.2021.3065019

[14]

10.1109/cvpr52688.2022.01660

[15]

10.1109/tnnls.2021.3136866

[16]

10.1007/978-3-030-58523-5_40

[17]

10.5555/2969033.2969125

[18]

10.1007/978-3-030-58536-5_45

[19]

10.1109/iccv48922.2021.01495

[20]

10.1109/lra.2021.3056339

[21]

10.1109/iccv48922.2021.01529

[22]

Dinh "NICE: Non-linear independent components estimation" arXiv:1410.8516 (2014)

[23]

10.1109/cvpr46437.2021.00888

[24]

10.1109/tnnls.2021.3084143

[25]

10.1109/tnnls.2022.3152251

[26]

Ying "Do transformers really perform badly for graph representation?"

[27]

Social force model for pedestrian dynamics

Dirk Helbing, Péter Molnár

Physical Review E 10.1103/physreve.51.4282

[28]

Gaussian Process Dynamical Models for Human Motion

J.M. Wang, D.J. Fleet, A. Hertzmann

IEEE Transactions on Pattern Analysis and Machine... 10.1109/tpami.2007.1167

[29]

10.1007/978-3-540-75404-6_36

[30]

10.1109/cvpr.2009.5206641

[31]

10.1109/iccv.2009.5459260

[32]

10.1109/cvpr.2016.110

[33]

10.1109/tnnls.2020.2975837

[34]

10.1109/cvpr.2019.01236

[35]

10.1109/cvpr.2017.497

[36]

10.1109/tpami.2021.3050918

[37]

Chung "A recurrent latent variable model for sequential data"

[38]

Graves "Towards end-to-end speech recognition with recurrent neural networks"

[39]

Show and tell: A neural image caption generator

Oriol Vinyals, Alexander Toshev, Samy Bengio et al.

2015 IEEE Conference on Computer Vision and Patter... 10.1109/cvpr.2015.7298935

[40]

10.1109/cvpr42600.2020.00635

[41]

10.1609/aaai.v34i07.6943

[42]

10.1109/tip.2022.3175605

[43]

10.1109/tpami.2022.3222871

[44]

10.1145/3219819.3219890

[45]

10.1109/icnlp55136.2022.00078

[46]

10.1109/icra.2018.8460504

[47]

10.1109/iccv.2019.00637

[48]

10.1609/aaai.v35i2.16174

[49]

10.1109/cvpr.2019.01240

[50]

10.1109/iros40897.2019.8967822

Showing 50 of 73 references

Cited By

30

IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction

Jing Yang, Yuehai Chen · 2024

IEEE Transactions on Cybernetics

Metrics

30

Citations

73

References

Details

Published: Nov 01, 2024
Vol/Issue: 35(11)
Pages: 16504-16517
License: View

Authors

R

Rongqin Liang

Guangdong Key Laboratory of Intelligent Information Processing, College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

Y

Yuanman Li

Guangdong Key Laboratory of Intelligent Information Processing, College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

J

Jiantao Zhou

State Key Laboratory of Internet of Things for Smart City and the Department of Computer and Information Science, University of Macau, Bras Basah, Macau

X

Xia Li

Guangdong Key Laboratory of Intelligent Information Processing, College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

Funding

Natural Science Foundation of China Award: 62001304

Basic and Applied Basic Research Foundation of Guangdong Province Award: 2022A1515010645

Key Project of Shenzhen Science and Technology Plan Award: 20220810180617001

Foundation for Science and Technology Innovation of Shenzhen Award: RCBS20210609103708014

Open Research Project Program of the State Key Laboratory of Internet of Things for Smart City Award: SKLIoTSC(UM)-2021-2023/ORP/GA04/2022

Cite This Article

Rongqin Liang, Yuanman Li, Jiantao Zhou, et al. (2024). STGlow: A Flow-Based Generative Framework With Dual-Graphormer for Pedestrian Trajectory Prediction. IEEE Transactions on Neural Networks and Learning Systems, 35(11), 16504-16517. https://doi.org/10.1109/tnnls.2023.3294998

STGlow: A Flow-Based Generative Framework With Dual-Graphormer for Pedestrian Trajectory Prediction

You May Also Like