(Fewshot detection)Review:RepMet: Representative-based metric learning for few-shot detection
Ref 官方代碼 MxNet pytorch Reimplement 確實detection部分 Something About Few-shot Detection 從圖1中可以看出，本文中的few-shot detection中的detection並不是完整的detection過程，文章中的大致意思是：讓現有的檢測模型框架的 classification head 變得可以學習Distance
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相關文章
- 1. (Few-shot Detection)Review: fewshot adaptive faster r-cnn
- 2. Similarity Metric Learning for Face Recognition2013
- 3. Ranked List Loss for Deep Metric Learning
- 4. Learning to Measure Changes: Fully Convolutional Siamese Metric Networks for Scene Change Detection
- 5. TADAM: Task dependent adaptive metric for improved few-shot learning閱讀筆記
- 6. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 7. TADAM:Task dependent adaptive metric for improved few-shot learning
- 8. MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
- 9. Learning Region Features for Object Detection
- 10. 論文閱讀筆記《RepMet Representative-based metric learning for classification and few-shot object detection》