论文阅读笔记 | (ECCV 2018) Learning to Navigate for Fine-grained Classification
论文来自北京大学，做细粒度图像分类。 论文下载：Learning to Navigate for Fine-grained Classification Abstract 由于找出判别特征比较困难，细粒度图像分类具有挑战性。找到完全表征对象的那些微妙特征并不简单。为了处理这种情况，文章提出了一种新颖的自我监督（self-supervision ）机制，可以有效地定位信息区域而无需边界框/部分注释（
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- 1. 论文阅读笔记 | (ECCV 2018) Learning to Navigate for Fine-grained Classification
- 2. 论文阅读笔记《Learning to Select Base Classes for Few-shot Classification》
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- 9. 论文阅读笔记《Dense Classification and Implanting for Few-Shot Learning》
- 10. 论文阅读笔记《Meta-SGD: Learning to Learn Quickly for Few-Shot Learning》