Complex-YOLO: An Euler-Region-Proposal for Real-time 3D Object Detection on Point Clouds
Complex-YOLO: An Euler-Region-Proposal for Real-time 3D Object Detection on Point Clouds 簡介 3D目標檢測整體框架 點雲預處理 網絡結構 E-RPN Anchor Box Loss 簡介 在這項工作中，作者通過特定的複數迴歸策略擴展了YOLOv2(一個用於RGB圖像的快速2D目標檢測網絡)，來在笛卡爾空間中估
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相關文章
- 1. PointPillars: Fast Encoders for 3D Object Detection from Point Clouds
- 2. 【3D計算機視覺】Deep Hough Voting for 3D Object Detection in Point Clouds
- 3. PIXOR Real-time 3D Object Detection from Point Clouds
- 4. [點雲目標檢測]-A Hierarchical Graph Network for 3D Object Detection on Point Clouds
- 5. Deep Hough Voting for 3D Object Detection in Point Clouds 論文筆記
- 6. 3D Point Clouds-1
- 7. RepPoints: Point Set Representation for Object Detection
- 8. 【論文閱讀】SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds
- 9. 【論文閱讀】【3D目標檢測】StarNet: Targeted Computation for Object Detection in Point Clouds
- 10. Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient CNN論文綜述（2016）