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Point Attention Network for Semantic Segmentation of 3D Point Clouds
Convolutional Neural Networks (CNNs) have performed extremely well on data represented by regularly arranged grids such as images. However, directly leveraging the classic... -
RueMonge2014
The dataset used in this paper for 3D point cloud classification and semantic segmentation tasks. -
2D-3D-S dataset
The 2D-3D-S dataset is an indoor dataset with multiple modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. -
ModelNet-10
The ModelNet-10 dataset is a benchmark for 3D point cloud classification and semantic segmentation. It contains 4,899 untextured CAD models divided into 10 categories. -
ModelNet40
Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...