[論文解讀]Multi-View 3D Object Detection Network for Autonomous Driving
問題引入 在無人駕駛場景中，物體的3D檢測(或者說是bounding-box)的重要性不言而喻。從2D檢測到3D檢測，主要的難點是提取深度信息，因此總體上可以將其分爲四種，分別爲： 基於單目圖像(Mono) 基於雙目圖像(Stereo) 基於雷達(LIDAR) 基於融合網絡 這篇論文就是一篇較爲出色的融合網絡的範例。後期和清華的老師溝通得知，這篇論文的算法正在被產業化，因此源碼在一段時間內不會透露
相關文章
- 1. Multi-View 3D Object Detection Network for Autonomous Driving
- 2. 論文閱讀CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 3. 解讀ECCV2020：Pillar-based Object Detection for Autonomous Driving
- 4. Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 5. Pillar-based Object Detection for Autonomous Driving
- 6. 【3D目標檢測】Multi-View 3D Object Detection Network for Autonomous Driving論文綜述（2016）
- 7. MV3D：Multi-View 3D Object Detection Network for Autonomous Driving（翻譯）
- 8. MODNet-Motion and Appearance based Moving Object Detection Network for Autonomous Driving
- 9. 每天一篇論文 373/1000 PSEUDO-LIDAR++:ACCURATE DEPTH FOR 3D OBJECT DETECTION IN AUTONOMOUS DRIVING
- 10. 每天一篇論文 324/365RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving
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相關文章
- 1. Multi-View 3D Object Detection Network for Autonomous Driving
- 2. 論文閱讀CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 3. 解讀ECCV2020：Pillar-based Object Detection for Autonomous Driving
- 4. Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 5. Pillar-based Object Detection for Autonomous Driving
- 6. 【3D目標檢測】Multi-View 3D Object Detection Network for Autonomous Driving論文綜述（2016）
- 7. MV3D：Multi-View 3D Object Detection Network for Autonomous Driving（翻譯）
- 8. MODNet-Motion and Appearance based Moving Object Detection Network for Autonomous Driving
- 9. 每天一篇論文 373/1000 PSEUDO-LIDAR++:ACCURATE DEPTH FOR 3D OBJECT DETECTION IN AUTONOMOUS DRIVING
- 10. 每天一篇論文 324/365RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving