[论文解读] 3DOP: 3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
基本介绍 3DOP这篇文章是当下使用双目相机进行3D bounding-box效果做好的方法，其是Fast RCNN方法在3D领域之内的拓展。由于原论文发表于NIPS15，出于Fast RCNN的效果并没有Faster RCNN和基于回归的方法好，且远远达不到实时性，因此其处理一张图片的时间达到了4.0s。 以下文章的介绍将主要依据资料更为完成的PAMI17来分析。 总体结构 如下则是该方法的总体
相关文章
- 1. 论文阅读CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 2. 论文解读：R-CNN《Rich feature hierarchies for accurate object detection and semantic segmentation》
- 3. Object Detection · RCNN论文解读
- 4. Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 5. 【论文阅读】Rich feature hierarchies for accurate object detection and semantic segmentation
- 6. 【论文阅读笔记】Rich feature hierarchies for accurate object detection and semantic segmentation
- 7. Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
- 8. Object Detection[论文合集]
- 9. [论文解读]Multi-View 3D Object Detection Network for Autonomous Driving
- 10. Acquistion Location Confidence for accurate object detection
- 更多相关文章...
- • XSL-FO instream-foreign-object 对象 - XSL-FO 教程
- • C# 文本文件的读写 - C#教程
- • JDK13 GA发布：5大特性解读
- • Scala 中文乱码解决
相关标签/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。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 论文阅读CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 2. 论文解读：R-CNN《Rich feature hierarchies for accurate object detection and semantic segmentation》
- 3. Object Detection · RCNN论文解读
- 4. Stereo R-CNN based 3D Object Detection for Autonomous Driving
- 5. 【论文阅读】Rich feature hierarchies for accurate object detection and semantic segmentation
- 6. 【论文阅读笔记】Rich feature hierarchies for accurate object detection and semantic segmentation
- 7. Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
- 8. Object Detection[论文合集]
- 9. [论文解读]Multi-View 3D Object Detection Network for Autonomous Driving
- 10. Acquistion Location Confidence for accurate object detection