《Learning Rich Features at High-Speed for Single-Shot Object Detection》笔记
Introduction 论文针对目前一阶段目标检测方法在小物体检测的表现弱的问题，提出了一个新的一阶段目标检测框架。该框架主要的思路是在特征金字塔的过程中融入缺少的低级/中级特征，让低、中、高特征在各个级别的特征层上流动。另外，考虑到目标检测框架从头开始训练的效果更好，该框架结合了预训练模型微调和从头开始训练的优点。 Method 该框架的整体结构如下 该框架包括SSD框架，light-weig
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相关文章
- 1. 【论文笔记】：Learning Rich Features at High-Speed for Single-Shot Object Detection
- 2. Learning Rich Features at High-Speed for Single-Shot Object Detection 论文笔记
- 3. 论文笔记：Learning Region Features for Object Detection
- 4. Learning Region Features for Object Detection
- 5. Learning Rich Features from RGB-D Images for Object Detection and Segmentation(ECCV2014)
- 6. Learning Rich Features for Image Manipulation Detection(CVPR 2018 图像篡改检测)
- 7. Feature Pyramid Networks for Object Detection 阅读笔记
- 8. 论文笔记：Rich feature hierarchies for accurate object detection and semantic segmentation
- 9. Object Detection《R-CNN》笔记（1）
- 10. Rich feature hierarchies for accurate object detection and semantic segmentation (RCNN)笔记