AI RESEARCH
TSM-Pose: Topology-Aware Learning with Semantic Mamba for Category-Level Object Pose Estimation
arXiv CS.CV
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ArXi:2604.16954v1 Announce Type: new Category-level object pose estimation is fundamental for embodied intelligence, yet achieving robust generalization to unseen instances remains challenging. However, existing methods mainly rely on simple feature extraction and aggregation, which struggle to capture category-shared topological structures and conduct semantic keypoint modeling, limiting their generalization. To address these, we propose a \textbf{T}opology-Aware Learning with \textbf{S}emantic \textbf{M}amba for Category-Level \textbf{P}ose Estimation framework (TSM-Pose). Specifically, we