Adversarial Feature Hallucination Networks for Few-Shot Learning

CVPR 2020 Kai LiYulun ZhangKunpeng LiYun Fu

The recent flourish of deep learning in various tasks is largely accredited to the rich and accessible labeled data. Nonetheless, massive supervision remains a luxury for many real applications, boosting great interest in label-scarce techniques such as few-shot learning (FSL), which aims to learn concept of new classes with a few labeled samples... (read more)

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