A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

Introduction: 3D Geometric Graph Neural Networks (GNNs) have emerged as transformative tools for modeling molecular data. Despite their predictive power, these models often suffer from limited ...

Recent geometric deep learning works define convolution operations in local regions and have enjoyed remarkable success on non-Euclidean data, including graph and point clouds. However, the high-level ...

As intelligent and interconnected vehicles continue to progress, the importance of 3D LiDAR sensors in traffic perception is increasing. Accurate 3D object detection in point clouds is crucial for ...

This paper introduces a High-Resolution Graph Convolutional Network (HR-GCN) designed to address the challenges of 2D-3D whole-body pose estimation. The proposed HR-GCN leverages the structural ...