A Closer Look at Few-shot Classification
@article{Chen2019ACL, title={A Closer Look at Few-shot Classification}, author={W. Chen and Y. Liu and Z. Kira and Y. Wang and Jia-Bin Huang}, journal={ArXiv}, year={2019}, volume={abs/1904.04232} }
Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples. [...] Key Method In this paper, we present 1) a consistent comparative analysis of several representative few-shot classification algorithms, with results showing that deeper backbones significantly reduce the performance differences among methods on datasets with limited domain differences, 2) a modified baseline method that surprisingly achieves competitive performance when compared…Expand Abstract
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