Instance-based adaptive attention algorithm for human-object interaction detection

Qing Ye; Xikun Wang

doi:10.1117/12.2671090

28 April 2023 Instance-based adaptive attention algorithm for human-object interaction detection

Qing Ye, Xikun Wang

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105E (2023) https://doi.org/10.1117/12.2671090
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Aiming at the problem of unclear human-object interaction behavior objects in complex background, we propose an Instance-Based Adaptive Attention (IBAA) algorithm. The algorithm adaptively generates a series of attention matrices according to the objects and subjects of human-object interaction instances. These attention matrices are then used to update the feature map to reduce the interference of the complex background. In order to enrich the human object interaction information, we use the graphical model to represent the interactions between human and objects and use the graph convolutional neural network to update it. Experimental results on HICO-DET dataset show that the proposed algorithm has significantly improved accuracy and multi-scale object detection ability compared with other human object interaction algorithms.

Citation Download Citation

Qing Ye and Xikun Wang "Instance-based adaptive attention algorithm for human-object interaction detection", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105E (28 April 2023); https://doi.org/10.1117/12.2671090

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