LDGCN: Linked Dynamic Graph CNN: Learning on PointCloud via Linking Hierarchical Features 2019 論文筆記
南方科技大學 代碼鏈接https://github.com/KuangenZhang/ldgcnn 本文是基於DGCNN和PointNet進行改進之後的工作，主要是用於點雲特徵提取任務，可以很方便的擴展到點雲分類和點雲分割任務。主要工作就是在DGCNN的基礎上加了不同層之間的skip connections，作者稱之爲"link",使得點雲分類精度有了0.7% 的提升，而且由於去掉了點雲變換網絡，
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相關文章
- 1. Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features 論文筆記 2020-10-06
- 2. Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features
- 3. Dynamic Graph CNN for Learning on Point Clouds 2019 論文筆記
- 4. Dynamic Graph CNN for Learning on Point Clouds 解析
- 5. 【論文筆記】DGCNN：Dynamic Graph CNN for Learning on Point Clouds
- 6. 【論文筆記】：Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training
- 7. 【論文筆記】Deep Learning on Graphs: A Survey
- 8. [論文筆記]EMNLP2019: Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks
- 9. Learning Hierarchical Features for Scene Labeling
- 10. Deep Learning on Graphs: A Survey論文筆記