3D Object Detection——Voxel based methods
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection VoxelNet 端到端的3D目標檢測網絡，且僅使用3D LIDAR 點雲數據就可以得到很好的精度。 網絡結構包含三個過程： 1. Feature learning network 構造3D 網格，對輸入的點雲數據柵格化。整個點雲的大立方體的深度、高度
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相關文章
- 1. 3D Object Detection——BEV-based methods
- 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. Image-based 3D Object Reconstruction
- 5. Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 6. Image-Based Object Spoofifing Detection
- 7. CornerNet-Lite: Efficient Keypoint-Based Object Detection
- 8. 解讀：PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
- 9. Pillar-based Object Detection for Autonomous Driving
- 10. An Introduction to CNN based Object Detection