Tanqiu Qiao tanqiu.qiao@durham.ac.uk
PGR Student Doctor of Philosophy
From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos
Qiao, Tanqiu; Li, Ruochen; Li, Frederick W B; Shum, Hubert P H
Authors
Ruochen Li ruochen.li@durham.ac.uk
PGR Student Doctor of Philosophy
Dr Frederick Li frederick.li@durham.ac.uk
Associate Professor
Professor Hubert Shum hubert.shum@durham.ac.uk
Professor
Abstract
Video-based Human-Object Interaction (HOI) recognition explores the intricate dynamics between humans and objects, which are essential for a comprehensive understanding of human behavior and intentions. While previous work has made significant strides, effectively integrating geometric and visual features to model dynamic relationships between humans and objects in a graph framework remains a challenge. In this work, we propose a novel end-to-end category to scenery framework, CATS, starting by generating geometric features for various categories through graphs respectively, then fusing them with corresponding visual features. Subsequently, we construct a scenery interactive graph with these enhanced geometric-visual features as nodes to learn the relationships among human and object categories. This methodological advance facilitates a deeper, more structured comprehension of interactions, bridging category-specific insights with broad scenery dynamics. Our method demonstrates state-of-the-art performance on two pivotal HOI benchmarks , including the MPHOI-72 dataset for multi-person HOIs and the single-person HOI CAD-120 dataset.
Citation
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 Proceedings of the 2024 International Conference on Pattern Recognition, Kolkata, India, 2024., Kolkata, India
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | Proceedings of the 2024 International Conference on Pattern Recognition, Kolkata, India, 2024. |
Start Date | Dec 1, 2024 |
End Date | Dec 5, 2024 |
Acceptance Date | Jul 1, 2024 |
Deposit Date | Jul 2, 2024 |
Journal | International Conference on Pattern Recognition |
Print ISSN | 1051-4651 |
Electronic ISSN | 2831-7475 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Public URL | https://durham-repository.worktribe.com/output/2514413 |
Publisher URL | https://ieeexplore.ieee.org/xpl/conhome/1000545/all-proceedings |
This file is under embargo due to copyright reasons.
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