從 Metric Learning 看 Few-Shot Semantic Segmentation
Few-Shot Segmentation 問題定義 假設模型在 C t r a i n C_{train} Ctrain 類上訓練，我們的目標是 在測試時，給定一些新類 C t e s t C_{test} Ctest 的有標籤的圖像，用這個 訓練好的 的模型對其他新類的圖像進行預測 (分割)。 一般文章中把上述有標籤的新類圖像稱爲 Support Image，把其他待分割的新類圖像成爲 Q
相關文章
- 1. Adversarial learning for semi-supervised semantic segmentation
- 2. 《Learning Dynamic Routing for Semantic Segmentation》
- 3. Learning Deconvolution Network for Semantic Segmentation
- 4. (Fewshot detection)Review:RepMet: Representative-based metric learning for few-shot detection
- 5. Review of Semantic Segmentation with Deep Learning
- 6. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 7. Learning to Adapt Structured Output Space for Semantic Segmentation——CVPR2018
- 8. Learning a Discriminative Feature Network for Semantic Segmentation
- 9. 18-Learning-a-Discriminative-Feature-Network-for-Semantic-Segmentation
- 10. Learning Deconvolution Network for Semantic Segmentation 筆記
- 更多相關文章...
- • 查看 XML 文件 - XML 教程
- • Git 查看提交歷史 - Git 教程
- • Composer 安裝與使用
- • Java Agent入門實戰（一）-Instrumentation介紹與使用
相關標籤/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。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Adversarial learning for semi-supervised semantic segmentation
- 2. 《Learning Dynamic Routing for Semantic Segmentation》
- 3. Learning Deconvolution Network for Semantic Segmentation
- 4. (Fewshot detection)Review:RepMet: Representative-based metric learning for few-shot detection
- 5. Review of Semantic Segmentation with Deep Learning
- 6. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 7. Learning to Adapt Structured Output Space for Semantic Segmentation——CVPR2018
- 8. Learning a Discriminative Feature Network for Semantic Segmentation
- 9. 18-Learning-a-Discriminative-Feature-Network-for-Semantic-Segmentation
- 10. Learning Deconvolution Network for Semantic Segmentation 筆記