|Short Name ||PointNet2_Demo|
|Long Name ||Semantic3D segmentation with Open3D and PointNet2|
|Description ||Demo project for Semantic3D (semantic-8) segmentation with Open3D and PointNet2.
The purpose of this demo project is to showcase the usage of Open3D in deep learning pipelines. Particularly, we used Open3D for
(1) Point cloud data loading, writing, and visualization. Open3D provides efficient implementations of various point cloud manipulation methods
(2) Data preprocessing, in particular, voxel-based downsampling
(3) Point cloud interpolation, in particular, fast nearest neighbor search for label interpolation.
The source code will be released soon at https://github.com/IntelVCL/Open3D-PointNet2-Semantic3D.
This project is based on the previous submission http://www.semantic3d.net/view_method_detail.php?method=pointnetpp_sem. We thank the authors for sharing the solution.|
|Reference ||https://github.com/IntelVCL/Open3D-PointNet2-Semantic3D, Yixing Lao|
|Hardware ||1 Titian X (Pascal), Intel(R) Core(TM) i7-6950X, 64 GB RAM|
|Used additional training data ||0|
|Last submission ||2018-12-04 07:49:49|
|Is opensource ||1|
|Number of submissions ||1|