Difference between revisions of "Point Cloud"
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[http://www.google.com/search?q=Point+Cloud+Convolutional+Neural+Network+CNN+deep+machine+learning+ML ...Google search] | [http://www.google.com/search?q=Point+Cloud+Convolutional+Neural+Network+CNN+deep+machine+learning+ML ...Google search] | ||
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* [http://github.com/NVlabs/splatnet SPLATNet: Sparse Lattice Networks for Point Cloud Processing | NVIDIA - GitHub] | * [http://github.com/NVlabs/splatnet SPLATNet: Sparse Lattice Networks for Point Cloud Processing | NVIDIA - GitHub] | ||
* [http://github.com/charlesq34/pointnet PointNet | C. Qi, H. Su, K. Mo, and L. Guibas - Stanford -GitHub] deep learning on point sets for 3D classification and segmentation | * [http://github.com/charlesq34/pointnet PointNet | C. Qi, H. Su, K. Mo, and L. Guibas - Stanford -GitHub] deep learning on point sets for 3D classification and segmentation | ||
* [http://stanford.edu/~rqi/pointnet2/ PointNet++: deep hierarchical feature learning on point sets in a metric space | C. Qi, L. Yi, H. Su, and L. Guibas - Stanford] | * [http://stanford.edu/~rqi/pointnet2/ PointNet++: deep hierarchical feature learning on point sets in a metric space | C. Qi, L. Yi, H. Su, and L. Guibas - Stanford] | ||
| + | * [http://arxiv.org/abs/1609.06666 Vote3Deep] | ||
| + | * [http://github.com/lijiannuist/Vote3Deep_lidar Vote3Deep LIDAR] | ||
| + | ** [http://github.com/BichenWuUCB/SqueezeSeg SqueezeSeg] | ||
* [[Screening; Passenger & Luggage]] | * [[Screening; Passenger & Luggage]] | ||
* [[3D Model]] e.g. [[3D Model#3DCNN | 3DCNN]] | * [[3D Model]] e.g. [[3D Model#3DCNN | 3DCNN]] | ||
| + | * [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]] | ||
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| + | A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. [A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. [http://en.wikipedia.org/wiki/Point_cloud Point Cloud] and [http://en.wikipedia.org/wiki/List_of_programs_for_point_cloud_processing List of programs for Point Cloud processing | Wikipedia] | ||
http://news.developer.nvidia.com/wp-content/uploads/2018/06/splatnet.png | http://news.developer.nvidia.com/wp-content/uploads/2018/06/splatnet.png | ||
Revision as of 11:49, 28 July 2019
Youtube search... ...Google search
- SPLATNet: Sparse Lattice Networks for Point Cloud Processing | NVIDIA - GitHub
- PointNet | C. Qi, H. Su, K. Mo, and L. Guibas - Stanford -GitHub deep learning on point sets for 3D classification and segmentation
- PointNet++: deep hierarchical feature learning on point sets in a metric space | C. Qi, L. Yi, H. Su, and L. Guibas - Stanford
- Vote3Deep
- Vote3Deep LIDAR
- Screening; Passenger & Luggage
- 3D Model e.g. 3DCNN
- Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. [A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. Point Cloud and List of programs for Point Cloud processing | Wikipedia
