Abstract: Multimodal 3D object detection significantly enhances perception by fusing LiDAR point clouds and RGB images. However, existing methods often fail to adaptively estimate modality confidence ...
Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
It's that time of the cricket season once again. The marquee match, the one rivalry that has claims to be the supreme one in world cricket. The one that's been held back by external forces, and now ...
A locally-made 3D animation YouTube channel is promoting ʻŌlelo Hawaiʻi educational videos to connect keiki and their ʻohana beyond the pae ʻāina. Nanea TV stands out as the only one on the platform ...
A windowed implementation of the iterative closest point (ICP) algorithm is used to calculate displacement and rotation fields from topographic point clouds that span a geologic event of interest.
In this paper, we present VoxT-GNN, an innovative framework that harnesses the strengths of both Transformer and Graph Neural Network architectures for 3D object detection from LiDAR point clouds.
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