3D Dental model segmentation with graph attentional convolution network

no code implementations • Pattern Recognition Letters 2021 • Yue Zhao, Lingming Zhang, Chongshi Yang, Yingyun Tan, Yang Liu, Pengcheng Li, Tianhao Huang, Chenqiang Gao

We have evaluated our network on a real-patient dataset of dental models acquired through 3D intraoral scanners, and experimental results show that our method outperforms state-of-the-art deep learning methods for 3D shape segmentation.

Segmentation