The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection
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Proceedings of IEEE International Conference on Computer Vision
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Social force model for pedestrian dynamics
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Social LSTM: Human Trajectory Prediction in Crowded Spaces
Alahi, A., Goel, K., Ramanathan, V., Robicquet, A., Fei-Fei, L., & Savarese, S. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.110 · Cited by 3,483
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
Williams, R. J. (1992) · Machine Learning · doi:10.1007/bf00992696 · Cited by 3,416
Recurrent Models of Visual Attention
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Trajectory clustering: a partition-and-group framework
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Theano: A CPU and GPU Math Compiler in Python
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Cited by
A Survey on Trajectory-Prediction Methods for Autonomous Driving
Huang, Y., Du, J., Yang, Z., Zhou, Z., Zhang, L., & Chen, H. (2022) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2022.3167103 · Cited by 677
Social Attention: Modeling Attention in Human Crowds
Vemula, A., Muelling, K., & Oh, J. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2018.8460504 · Cited by 675
STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction
Huang, Y., Bi, H., Li, Z., Mao, T., & Wang, Z. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00637 · Cited by 658
Human motion trajectory prediction: a survey
Rudenko, A., Palmieri, L., Herman, M., Kitani, K. M., Gavrila, D. M., & Arras, K. O. (2020) · The International Journal of Robotics Research · doi:10.1177/0278364920917446 · Cited by 658
Chen, C., Liu, Y., Kreiss, S., & Alahi, A. (2019) · 2019 International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2019.8794134 · Cited by 615
Metadata
- Authors
- Fernando, T., Denman, S., Sridharan, S., & Fookes, C.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2018-12
- Volume
- 108
- Pages
- 466-478
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2593239008
- Cited by
- 371
- References
- 27
- FWCI
- 35.16
- Type
- journal article
- Language
- en
- Open access
- green
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- Fernando, T., Denman, S., Sridharan, S., & Fookes, C. (2018). Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection. Neural Networks. https://doi.org/10.1016/j.neunet.2018.09.002
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
