(Few-shot detection)Review: Few-shot Object Detection via Feature Reweighting

时间 2021-01-02

标签 3.4 Few-Shot Learning 繁體版

原文原文链接

Ref feature reweighting pytorch Implement 1. 提出研究的问题对于few-shot分类而言，可以采用学习prototype的方式学习一个中心，但是如果用于目标检测，很难匹配和定位一个物体。因为在图像中会有很多的干扰因素和非目标物体。 2. 提出方案 Feature Extractor module Feature Extractor从 query ima

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1. Few-shot Object Detection via Feature Reweighting
2. ICCV 2019 Few-shot Object Detection via Feature Reweighting
3. Few-shot Object Detection via Feature Reweighting (ICCV2019)
4. (Few-shot Detection)Review: Fews-shot Object Detection Feature Reweighting
5. (Few-shot Detection)Review: fewshot adaptive faster r-cnn
6. Few-shot Object Detection via Feature Reweighting 论文笔记
7. 论文阅读笔记《Few-shot Object Detection via Feature Reweighting》
8. (Fewshot detection)Review:RepMet: Representative-based metric learning for few-shot detection
9. Object Detection 之Feature Pyramid Networks for Object Detection(FPN)
10. 【Feature Pyramid】《Deep Feature Pyramid Reconfiguration for Object Detection》
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1. Few-shot Object Detection via Feature Reweighting
2. ICCV 2019 Few-shot Object Detection via Feature Reweighting
3. Few-shot Object Detection via Feature Reweighting (ICCV2019)
4. (Few-shot Detection)Review: Fews-shot Object Detection Feature Reweighting
5. (Few-shot Detection)Review: fewshot adaptive faster r-cnn
6. Few-shot Object Detection via Feature Reweighting 论文笔记
7. 论文阅读笔记《Few-shot Object Detection via Feature Reweighting》
8. (Fewshot detection)Review:RepMet: Representative-based metric learning for few-shot detection
9. Object Detection 之Feature Pyramid Networks for Object Detection(FPN)
10. 【Feature Pyramid】《Deep Feature Pyramid Reconfiguration for Object Detection》

>>更多相关文章<<