| Short Name | OctreeNet_CRF |
| Long Name | OctreeNet_CRF |
| Website | |
| Description | A novel sparse convolutional neural network based on the octree for real-time point cloud classification. The proposed framework only uses the coordinates of 3D points which are direct outputs of standard laser scanners and no color information is involved. The submitted runtime includes the io time. The time costs for io and data construction, OctreeNet inference and CRF inference are 172.57s, 5.93s and 6.34s respectively. If multi-thread technology is used in the OctreeNet inference, the time cost can be reduced to 2.29s with our hardware. |
| Reference | F. Wang, Y. Zhuang, H. Gu, and H. Hu, OctreeNet：A Novel Sparse 3D Convolutional Neural Network for Real-time 3D Outdoor Scene Analysis, submitted to IEEE Transactions on Automation Science and Engineering. |
| Hardware | Intel® core(TM) CPU i5-4590 @ 3.3 GHZ, 8 GB RAM |
| Used additional training data | 0 |
| Last submission | 2017-12-13 07:26:36 |
| Is opensource | 0 |
| Number of submissions | 1 |
