论文阅读：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
论文名称：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 主要内容： 本文利用点云的无序性和旋转不变性，提出了一个深度网络，直接将点云的（x，y，z）坐标作为输入，根据网络结构的不同可以完成分类、目标部分分割和场景分割任务。 解决的问题： 神经网络通常处理的数据都是有规范格式的，例如图片，文本
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相关文章
- 1. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 论文笔记
- 2. Deep Learning on Point Sets for 3D Classification and Segmentation
- 3. 【论文阅读笔记】PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 4. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation解析(PointNet模型)
- 5. 2020.09.27读 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 6. [Point Cloud] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 论文解读
- 7. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 8. PointNet Deep Learning on Point Sets for 3D Classification and Segmentation
- 9. 《PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation》点网解析
- 10. [论文解读+复现] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation