CVPR2017_PointNet_ Deep Learning on Point Sets for 3D Classification and Segmentation
Author Charles R. Qi* Hao Su* @ Stanford 第一个是PHD, 第二个是Professor, 两人一直在一起做些3D的研究 还有个PointNet++ Abstract 点云是一种很重要的几何数据结构，因为它不规则的形式，很多研究都是将它转换成规则的3D体素或者collections,这样的话就会造成大量不必要的数据也会产生一些相应的问题。 点云最接近原始传感数
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相关文章
- 1. Deep Learning on Point Sets for 3D Classification and Segmentation
- 2. CVPR2017_PointNet_ Deep Learning on Point Sets for 3D Classification and Segmentation
- 3. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation解析(PointNet模型)
- 4. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 5. PointNet Deep Learning on Point Sets for 3D Classification and Segmentation
- 6. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 论文笔记
- 7. 《PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation》点网解析
- 8. 论文阅读：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 9. 2020.09.27读 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 10. 3D点云网络：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation