HOI-M3:Capture Multiple Humans and Objects Interaction within Contextual Environment
arxiv(2024)
摘要
Humans naturally interact with both others and the surrounding multiple
objects, engaging in various social activities. However, recent advances in
modeling human-object interactions mostly focus on perceiving isolated
individuals and objects, due to fundamental data scarcity. In this paper, we
introduce HOI-M3, a novel large-scale dataset for modeling the interactions of
Multiple huMans and Multiple objects. Notably, it provides accurate 3D tracking
for both humans and objects from dense RGB and object-mounted IMU inputs,
covering 199 sequences and 181M frames of diverse humans and objects under rich
activities. With the unique HOI-M3 dataset, we introduce two novel data-driven
tasks with companion strong baselines: monocular capture and unstructured
generation of multiple human-object interactions. Extensive experiments
demonstrate that our dataset is challenging and worthy of further research
about multiple human-object interactions and behavior analysis. Our HOI-M3
dataset, corresponding codes, and pre-trained models will be disseminated to
the community for future research.
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