Kai Zhai — accepted AI-conference papers

2024

A Global-Local Graph Attention Network for Deformable Linear Objects Dynamic Interaction With Environment

Jian Chu, Wenkang Zhang, Bo Ouyang, Kunmiao Tian, Shuai Zhang, Kai Zhai

RA-L 2024

Accurately modeling the interactions between deformable linear objects (DLOs) and their environments is crucial for active deformation control by robot manipulators. Graph Neural Networks (GNNs) have shown immense potential in the particle-based dynamics of DLOs. However, most existing studies propa

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2023

HopFIR: Hop-wise GraphFormer with Intragroup Joint Refinement for 3D Human Pose Estimation

Kai Zhai, Qiang Nie, Bo Ouyang, Xiang Li, Shanlin Yang

ICCV 2023poster

2D-to-3D human pose lifting is fundamental for 3D human pose estimation (HPE), for which graph convolutional networks (GCNs) have proven inherently suitable for modeling the human skeletal topology. However, the current GCN-based 3D HPE methods update the node features by aggregating their neighbors…

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