《Cascade R-CNN: Delving into High Quality Object Detection》论文解析
今年的图像领域的顶会CVPR收录了很多目标检测的论文，Cascade R-CNN: Delving into High Quality Object Detection这篇文章关注的是IOU的最优选择，很小的trick，不过在效果上有不错的提高。git 摘要 目标检测中，须要肯定IOU的阈值来区分正样本和负样本。低的阈值如0.5训练网络，易产生检测噪声，但随着IOU阈值的增长，检测性能会下降。两个
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相关文章
- 1. [论文阅读]Cascade RCNN|Cascade R-CNN: Delving into High Quality Object Detection
- 2. 《Cascade R-CNN: Delving into High Quality Object Detection》论文解析
- 3. Cascade R-CNN: Delving into High Quality Object Detection
- 4. 论文：Cascade R-CNN: Delving into High Quality Object Detection 阅读笔记
- 5. 【论文阅读笔记】Cascade R-CNN: Delving into High Quality Object Detection
- 6. 论文阅读：Cascade R-CNN: Delving into High Quality Object Detection
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- 8. Cascade R-CNN: Delving into High Quality Object Detection 论文笔记
- 9. 《Cascade R-CNN: Delving into High Quality Object Detection》论文笔记
- 10. Face Paper：Cascade R-CNN: Delving into High Quality Object Detection