A Skeleton-Aware Graph Convolutional Network for Human-Object Interaction Detection

Manli Zhu, Edmond S. L. Ho and Hubert P. H. Shum
Proceedings of the 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2022

A Skeleton-Aware Graph Convolutional Network for Human-Object Interaction Detection

Abstract

Detecting human-object interactions is essential for comprehensive understanding of visual scenes. In particular, spatial connections between humans and objects are important cues for reasoning interactions. To this end, we propose a skeleton-aware graph convolutional network for human-object interaction detection, named SGCN4HOI. Our network exploits the spatial connections between human keypoints and object keypoints to capture their fine-grained structural interactions via graph convolutions. It fuses such geometric features with visual features and spatial configuration features obtained from human-object pairs. Furthermore, to better preserve the object structural information and facilitate human-object interaction detection, we propose a novel skeleton-based object keypoints representation. The performance of SGCN4HOI is evaluated in the public benchmark V-COCO dataset. Experimental results show that the proposed approach outperforms the state-of-the-art pose-based models and achieves competitive performance against other models.

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BibTeX

@inproceedings{zhu22skeleton,
 author={Zhu, Manli and Ho, Edmond S. L. and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2022 IEEE International Conference on Systems, Man, and Cybernetics},
 series={SMC '22},
 title={A Skeleton-Aware Graph Convolutional Network for Human-Object Interaction Detection},
 year={2022},
 month={10},
 pages={275--281},
 numpages={7},
 doi={10.1109/SMC53654.2022.9945149},
 publisher={IEEE},
 location={Prague, Czech Republic},
}

RIS

TY  - CONF
AU  - Zhu, Manli
AU  - Ho, Edmond S. L.
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2022 IEEE International Conference on Systems, Man, and Cybernetics
TI  - A Skeleton-Aware Graph Convolutional Network for Human-Object Interaction Detection
PY  - 2022
Y1  - 10 2022
SP  - 275
EP  - 281
DO  - 10.1109/SMC53654.2022.9945149
PB  - IEEE
ER  - 

Plain Text

Manli Zhu, Edmond S. L. Ho and Hubert P. H. Shum, "A Skeleton-Aware Graph Convolutional Network for Human-Object Interaction Detection," in SMC '22: Proceedings of the 2022 IEEE International Conference on Systems, Man, and Cybernetics, pp. 275-281, Prague, Czech Republic, IEEE, Oct 2022.

Supporting Grants

Northumbria University

Postgraduate Research Scholarship (Ref: ): £65,000, Principal Investigator ()
Received from Faculty of Engineering and Environment, Northumbria University, UK, 2020-2022
Project Page

Similar Research

Manli Zhu, Edmond S. L. Ho, Longzhi Yang and Hubert P. H. Shum, "Geometric Features Enhanced Human-Object Interaction Detection", IEEE Transactions on Instrumentation and Measurement (TIM), 2024
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Qianhui Men, Howard Leung, Edmond S. L. Ho and Hubert P. H. Shum, "A Two-Stream Recurrent Network for Skeleton-Based Human Interaction Recognition", Proceedings of the 2020 International Conference on Pattern Recognition (ICPR), 2020
Ying Huang, Hubert P. H. Shum, Edmond S. L. Ho and Nauman Aslam, "High-Speed Multi-Person Pose Estimation with Deep Feature Transfer", Computer Vision and Image Understanding (CVIU), 2020

 

 

Last updated on 10 June 2024
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