Asymmetric Distribution Measure for Few-shot Learning

1 Feb 2020Wenbin LiLei WangJing HuoYinghuan ShiYang GaoJiebo Luo

The core idea of metric-based few-shot image classification is to directly measure the relations between query images and support classes to learn transferable feature embeddings. Previous work mainly focuses on image-level feature representations, which actually cannot effectively estimate a class's distribution due to the scarcity of samples... (read more)

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