《PointNet：Deep Learning on Point Sets for 3D Classification and Segmentation》中文翻譯
PointNet：用於3D分類和分割的點集的深度學習 摘要：點雲是幾何數據結構的重要類型。 因爲其格式不規則，大多數研究人員將這些數據轉換爲規則的三維體素網格或圖像集合。 可是，這會致使數據沒必要要的龐大並致使問題。 在本文中，咱們設計了一種直接消耗點雲的新型神經網絡，它很好地尊重了輸入點中的點的置換不變性。 咱們的網絡，名爲PointNet，提供了從對
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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 Classificatiion and Segmentation
- 3. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文筆記
- 4. 論文閱讀：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 5. 3D點雲網絡：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation
- 6. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation解析(PointNet模型)
- 7. CVPR2017_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
- 10. 《PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation》點網解析