Staff profile

Conference Paper

• From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos
  
  Qiao, T., Li, R., Li, F. W. B., & Shum, H. P. H. (2025). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. In Pattern Recognition 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XV (pp. 262-277). Springer. https://doi.org/10.1007/978-3-031-78354-8_17
• TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training
  
  Li, L., Qiao, T., Shum, H. P. H., & Breckon, T. P. (2024). TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training. In Proceedings of the 35th British Machine Vision Conference. British Machine Vision Association.
• Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos
  
  Qiao, T., Men, Q., Li, F. W., Kubotani, Y., Morishima, S., & Shum, H. P. (2022). Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos. In Lecture Notes in Computer Science (pp. 474-491). Springer Verlag. https://doi.org/10.1007/978-3-031-19772-7_28

Journal Article

• Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
  
  Li, R., Qiao, T., Katsigiannis, S., Zhu, Z., & Shum, H. P. (2025). Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. IEEE Transactions on Circuits and Systems for Video Technology. Advance online publication. https://doi.org/10.1109/TCSVT.2025.3539522