【論文筆記】【點雲分割】2018_PointSIFT：A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation
PointSIFT：A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation 0. Summary 本文提出了pointSIFT方法，通過PointSIFT和PointNet++相結合構建了網絡結構。PointSIFT借鑑了SIFT的思想，在空間上進行八個方向的臨近點查詢，並進行xyz方向的卷積得到空間特徵，並在實驗部分
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相關文章
- 1. Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation
- 2. [點雲分割]-Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds
- 3. 論文筆記-PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud
- 4. 《Learning Deconvolution Network for Semantic Segmentation》論文筆記
- 5. 論文筆記：Learning Deconvolution Network for Semantic Segmentation
- 6. 【論文筆記】Learning Deconvolution Network for Semantic Segmentation
- 7. PF-Net: Point Fractal Network for 3D Point Cloud Completion 2020 論文筆記
- 8. 【點雲語義分割】Multi-Path Region Mining ForWeakly Supervised 3D Semantic Segmentation on Point Clouds（CVPR）
- 9. [譯文] PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud
- 10. 【譯文】 PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud