AI RESEARCH
Multimodal Graph Network Modeling for Human-Object Interaction Detection with PDE Graph Diffusion
arXiv CS.CV
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ArXi:2509.12554v3 Announce Type: replace Existing GNN-based Human-Object Interaction (HOI) detection methods rely on simple MLPs to fuse instance features and propagate information. However, this mechanism is largely empirical and lack of targeted information propagation process. To address this problem, we propose Multimodal Graph Network Modeling (MGNM) for HOI detection with Partial Differential Equation (PDE) graph diffusion. Specifically, we first design a multimodal graph network framework that explicitly models the HOI detection task within a four-stage graph structure.