Jiaying Zhang, Xiaoli Zhao, Zheng Chen. Review of Semantic Segmentation of Point Cloud Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2020, 57(4): 040002
- Laser & Optoelectronics Progress
- Vol. 57, Issue 4, 040002 (2020)
![Fine-grained annotations of 24 objects in the PartNet dataset[26]](/richHtml/lop/2020/57/4/040002/img_1.jpg)
Fig. 1. Fine-grained annotations of 24 objects in the PartNet dataset[26]
![Models of chairs and laptops in the ShapeNet Part dataset[28]](/richHtml/lop/2020/57/4/040002/img_2.jpg)
Fig. 2. Models of chairs and laptops in the ShapeNet Part dataset[28]
![Point cloud scene and semantic segmentation diagram in S3DIS dataset[29]](/Images/icon/loading.gif){kind=icon}
Fig. 3. Point cloud scene and semantic segmentation diagram in S3DIS dataset[29]
Fig. 4. Annotated indoor scene maps in ScanNet dataset[30]
Fig. 5. Examples of Semantic3D dataset[31]. (a) Point cloud scene; (b) diagram of intensity; (c) diagram of semantic segmentation
Fig. 6. Semantic segmentation results of outdoor scene in vKITTI dataset[32]
Fig. 7. Visual representation of point cloud semantic segmentation methods
Fig. 8. Framework of multi-view convolutional neural network (MVCNN)[37]
Fig. 9. Overall flow of semantic marks of SnapNet-R network [39]
Fig. 10. Overall architecture of semantic segmentation network of SEGCloud[49]
Fig. 11. Framework of PointNet for point cloud classification and segmentation[16]
Fig. 12. Overall framework of RSNet for point cloud semantic segmentation[53]
Fig. 13. Point cloud semantic segmentation network of SO-Net formed by SOM[54]
Fig. 14. Applications of hierarchical convolution in regular gird and point clouds, and PointCNN framework used for semantic segmentation[18]. (a) Application of hierarchical convolution; (b) PointCNN framework
Fig. 15. Architecture of PointNet++ for point cloud classification and segmentation[17]
Fig. 16. Overall architectures of PointSIFT module and point segementation of PointSIFT[58]. (a) Structure; (b) whole architecture
Fig. 17. Architecture of A-CNN for point cloud classification and segmentation[61]
Fig. 18. Point cloud semantic segmentation network of 3DMAX-Net[60] (MS-FLB: multi-scale feature learning block; LGAB: local and global feature aggregation block)
Fig. 19. Framework of 3P-RNN for point cloud semantic segmentation[62]
Fig. 20. Network structural diagram of LDGCNN for point cloud classification and segmentation[65]
Fig. 21. Network structural diagram of RGCNN for point cloud classification and segmentation[67]
Fig. 22. Network framework of GAPNet for point cloud semantic segmentation[68]
Fig. 23. Forward time of different network models
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Table 1. Common datasets of point cloud segmentation
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Table 2. Network parameter quantity of different semantic segmentation models
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Table 3. Segmentation results of different models on typical point cloud datasets
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