Semantic Feature Augmentation in Few-shot Learning

    arXiv: Computer Vision and Pattern Recognition, Volume abs/1804.05298, 2018.

    Cited by: 22|Bibtex|Views22|Links
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    Abstract:

    A fundamental problem with few-shot learning is the scarcity of data in training. A natural solution to alleviate this scarcity is to augment the existing images for each training class. However, directly augmenting samples in image space may not necessarily, nor sufficiently, explore the intra-class variation. To this end, we propose to ...More

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