Paper4：Voxel-Based Extraction and Classification of 3-D Pole-Like Object From Mobile LIDAR Point Clo
Voxel-Based Extraction and Classification of 3-D Pole-Like Object From Mobile LIDAR Point Cloud Data 車載點雲中3維桿狀目標基於體素的提取與分類 摘要： 道路環境數字測繪是道路基礎設施清查和城市規劃的一項重要任務。對類杆目標的自動提取和分類，可以顯著地降低和提高工作效率。因此，本文提出了一種基於體素
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相關文章
- 1. LiDAR 3D Object Detetcion
- 2. BirdNet: a 3D Object Detection Framework from LiDAR information
- 3. 3D Machine Learning Single Object Classification
- 4. Deep Learning on Point Sets for 3D Classification and Segmentation
- 5. LiDAR Textbook & Automated Road Network Extraction
- 6. 3D點雲網絡：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation
- 7. 《Point Feature Extraction on 3D Range Scans Taking into Account Object Boundaries》——譯文
- 8. CVPR2017_PointNet_ Deep Learning on Point Sets for 3D Classification and Segmentation
- 9. PointPillars: Fast Encoders for 3D Object Detection from Point Clouds
- 10. PIXOR Real-time 3D Object Detection from Point Clouds