Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss

時間 2020-12-26

標籤 3d bouding box 简体版

原文原文鏈接

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

>>阅读原文<<

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
更多相關文章...
• XSL-FO instream-foreign-object 對象 - XSL-FO 教程
• W3C RDF and OWL 活動 - W3C 教程
• RxJava操作符（七）Conditional and Boolean
• RxJava操作符（六）Utility

相關標籤/搜索

每日一句

每一个你不满意的现在，都有一个你没有努力的曾经。

最新文章

1. springboot在一個項目中啓動多個核心啓動類
2. Spring Boot日誌-3 ------＞SLF4J與別的框架整合
3. SpringMVC-Maven（一）
4. idea全局設置
5. 將word選擇題轉換成Excel
6. myeclipse工程中library 和 web-inf下lib的區別
7. Java入門——第一個Hello Word
8. 在chrome安裝vue devtools（以及安裝過程中出現的錯誤）
9. Jacob線上部署及多項目部署問題處理
10. 1.初識nginx

本站公眾號

歡迎關注本站公眾號,獲取更多信息

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

>>更多相關文章<<