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arXiv · 2508.17270

Spatial-Temporal Human-Object Interaction Detection

Xu Sun·Yunqing He·Tongwei Ren·Gangshan Wu
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Abstract

In this paper, we propose a new instance-level human-object interaction detection task on videos called ST-HOID, which aims to distinguish fine-grained human-object interactions (HOIs) and the trajectories of subjects and objects. It is motivated by the fact that HOI is crucial for human-centric video content understanding. To solve ST-HOID, we propose a novel method consisting of an object trajectory detection module and an interaction reasoning module. Furthermore, we construct the first dataset named VidOR-HOID for ST-HOID evaluation, which contains 10,831 spatial-temporal HOI instances. We conduct extensive experiments to evaluate the effectiveness of our method. The experimental results demonstrate that our method outperforms the baselines generated by the state-of-the-art methods of image human-object interaction detection, video visual relation detection and video human-object interaction recognition.

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Xu Sun, Yunqing He, Tongwei Ren, Gangshan Wu. 2025-08-24. Spatial-Temporal Human-Object Interaction Detection. https://arxiv.org/abs/2508.17270

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