1 INTRODUCTION  
2 BACKGROUND  
2.1 Basic concepts  
2.2 Common 3D understanding tasks  
2.3 Relevant surveys  
4 COMMON DEEP ARCHITECTURES  
4.1 Point-based deep architectures  
4.2 Graph-based deep architectures  
4.3 Sparse voxel-based deep architectures  
4.4 Spatial CNN-based deep architectures  
4.5 Transformer-based deep architectures  
5 UNSUPERVISED POINT CLOUD REPRESENTATION LEARNING  
5.1 Generation-based methods  
5.2 Context-based methods  
5.3 Multiple modal-based methods  
5.4 Local descriptor-based methods  
5.5 Pros and Cons  
6 BENCHMARK PERFORMANCES  
6.1 Evaluation Criteria  
6.2 Object-level tasks  
6.3 Scene-level tasks  
7 FUTURE DIRECTION  
8 CONCLUSION