論文閱讀：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
論文名稱：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 主要內容： 本文利用點雲的無序性和旋轉不變性，提出了一個深度網絡，直接將點雲的（x，y，z）座標作爲輸入，根據網絡結構的不同可以完成分類、目標部分分割和場景分割任務。 解決的問題： 神經網絡通常處理的數據都是有規範格式的，例如圖片，文本
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相關文章
- 1. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文筆記
- 2. Deep Learning on Point Sets for 3D Classification and Segmentation
- 3. 【論文閱讀筆記】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讀 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 論文解讀
- 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》點網解析
- 10. [論文解讀+復現] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation