AI RESEARCH
PCFEx: Point Cloud Feature Extraction for Graph Neural Networks
arXiv CS.CV
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ArXi:2603.08540v1 Announce Type: new Graph neural networks (GNNs) have gained significant attention for their effectiveness across various domains. This study focuses on applying GNN to process 3D point cloud data for human pose estimation (HPE) and human activity recognition (HAR). We propose novel point cloud feature extraction (PCFEx) techniques to capture meaningful information at the point, edge, and graph levels of the point cloud by considering point cloud as a graph. Moreover, we