从 Metric Learning 看 Few-Shot Semantic Segmentation

时间 2021-01-18

标签机器学习深度学习神经网络 Metric Learning Few-Shot One-Shot 繁體版

原文原文链接

Few-Shot Segmentation 问题定义假设模型在 C t r a i n C_{train} Ctrain 类上训练，我们的目标是在测试时，给定一些新类 C t e s t C_{test} Ctest 的有标签的图像，用这个训练好的的模型对其他新类的图像进行预测 (分割)。一般文章中把上述有标签的新类图像称为 Support Image，把其他待分割的新类图像成为 Q

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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 笔记

>>更多相关文章<<