Few-shot meta-learning has been recently reviving with expectations to mimic humanity's fast adaption to new concepts based on prior knowledge. In this short communication, we give a concise review on recent representative methods in few-shot meta-learning, which are categorized into four branches according to their technical characteristics. We conclude this review with some vital current challenges and future prospects in few-shot meta-learning.
@article{arxiv.2005.10953,
title = {A Concise Review of Recent Few-shot Meta-learning Methods},
author = {Xiaoxu Li and Zhuo Sun and Jing-Hao Xue and Zhanyu Ma},
journal= {arXiv preprint arXiv:2005.10953},
year = {2020}
}