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[論文解讀+復現] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
時間 2020-12-23
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點雲論文閱讀筆記
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一、摘要 本文提出了一種結構簡單的物體檢測與點雲分割、語義分析的深度學習網絡,網絡具有置換不變性,文章最後對網絡的魯棒性做出瞭解釋。 二、介紹 典型卷積網絡需要規則的輸入,例如像素和體素,目的是可以共享權重參數(weight),一些研究學者會將點雲轉化爲體素或者圖像集再傳入神經網絡,
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相關文章
1.
論文閱讀:PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
2.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文筆記
3.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation解析(PointNet模型)
4.
[Point Cloud] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文解讀
5.
Deep Learning on Point Sets for 3D Classification and Segmentation
6.
2020.09.27讀 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
7.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
8.
《PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation》點網解析
9.
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【論文閱讀筆記】PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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