PointNet Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Abstract 由於點雲數據的無序性，大多數研究者把它轉化爲規則的 3D 體素網格或者轉化爲圖像數據集來處理。這樣會不必要的增大數據集並且產生一些（像素點失真）問題。本文作者設計了一個新的網絡，直接處理點雲數據。 1、Introduction
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- 7. 2020.09.27讀 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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相關文章
- 1. Deep Learning on Point Sets for 3D Classification and Segmentation
- 2. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation解析(PointNet模型)
- 3. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 4. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文筆記
- 5. 《PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation》點網解析
- 6. 論文閱讀：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 7. 2020.09.27讀 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 8. CVPR2017_PointNet_ Deep Learning on Point Sets for 3D Classification and Segmentation
- 9. [Point Cloud] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文解讀
- 10. 3D點雲網絡：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation