A robust transductive distribution calibration method for few-shot learning

Jingcong Li, Chunjin Ye, Fei Wang, Jiahui Pan

Abstract: Highlights•We analyze the existing issues with feature distribution estimation in few-shot image classification.•A novel method is proposed to estimate the few-shot class distribution in a more accurate and robust way.•Extensive experiments demonstrate the effectiveness of the proposed method.