《Point Feature Extraction on 3D Range Scans Taking into Account Object Boundaries》——譯文
本文是對 邊界提取、NARF 論文的翻譯，非正式翻譯，僅供個人學習理解，文中很多邏輯思想部分還不甚明晰，或是部分術語翻譯不夠準確，還望與更多的人一起探討； 翻譯文檔來源：https://www.researchgate.net/publication/221069159_Point_feature_extraction_on_3D_range_scans_taking_into
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相關文章
- 1. Taking into account the utilization rate of these four
- 2. 【論文速覽】PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
- 3. 一文讀懂PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
- 4. 01_kaggle - Using a 3D Convolutional Neural Network on medical imaging data (CT Scans) for Kaggle
- 5. 論文速看[2019-1-7]-Multi-scale tensor voting for feature extraction from unstructured point clouds
- 6. 解讀：PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
- 7. 《PointNet：Deep Learning on Point Sets for 3D Classification and Segmentation》中文翻譯
- 8. 3D點雲網絡：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation
- 9. Feature Preprocessing on Kaggle
- 10. [譯文] PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud