MMF-《Deep Continuous Fusion for Multi-Sensor 3D Object Detection》論文翻譯
《Deep Continuous Fusion for Multi-Sensor 3D Object Detection》論文翻譯 3 多層傳感器 3D 目標檢測 3.1連續融合層 3.2 多傳感器目標檢測網絡 這篇論文是CVPR2019年的論文，方法在KITTI數據集中的3D object detection上排名很高。創新點主要是第一次將圖像特徵投影到BEV圖做迴歸，其次是解決了BEV和Im
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相關文章
- 1. Deep Continuous Fusion for Multi-Sensor 3D Object Detection
- 2. Deep Neural Networks for Object Detection論文翻譯
- 3. 三維目標檢測論文閱讀：Deep Continuous Fusion for Multi-Sensor 3D Object Detection
- 4. 解讀：Deep Continuous Fusion for Multi-Sensor 3D Object Detection
- 5. 【論文翻譯】Focal Loss for Dense Object Detection
- 6. PointPainting: Sequential Fusion for 3D Object Detection論文學習及復現
- 7. Deep Continuous Fusion (Uber'18) - 知乎
- 8. 【論文速覽】PointPainting: Sequential Fusion for 3D Object Detection
- 9. Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation論文翻譯
- 10. 論文閱讀：Deep Neural Networks for Object Detection