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. (2024, December). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. Presented at ICPR 2024: International Conference on Pattern Recognition, Kolkata, India
• 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, November). TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training. Presented at BMVC'24: The 35th British Machine Vision Conference, Glasgow, UK
• 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, October). Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos. Presented at Computer Vision - ECCV 2022, Tel Aviv, Israel

Journal Article

• Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
  Li, R., Qiao, T., Katsigiannis, S., Zhu, Z., & Shum, H. P. (online). Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/TCSVT.2025.3539522
• Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos
  Qiao, T., Li, R., Li, F. W. B., Kubotani, Y., Morishima, S., & Shum, H. P. H. (2025). Geometric Visual Fusion Graph Neural Networks for Multi-Person Human-Object Interaction Recognition in Videos. Expert Systems with Applications, 290, Article 128344. https://doi.org/10.1016/j.eswa.2025.128344