Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss
Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss insights 3DIou loss Homoscedastic noise Heteroscedastic noise 3D框的representation 重要結論 distance 越遠其va
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相關文章
- 1. Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
- 2. Object-Detection-Loss
- 3. Improved Object Categorization and Detection Using Comparative Object Similarity
- 4. 【3D 目標檢測】2019 CVPR Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles
- 5. 3D Object Detection 3D目標檢測綜述
- 6. Localization and Object Detection
- 7. Focal Loss for Dense Object Detection
- 8. One-shot object detection
- 9. 論文閱讀：EfficientDet: Scalable and Efficient Object Detection
- 10. 3D Bounding Box Estimation Using Deep Learning and Geometry