Few-shot classification studies the problem of quickly adapting a deep learner to understanding novel classes based on few support images. In this context, recent research efforts have been aimed at designing more and complex classifiers that measure similarities between query images but left importance feature embeddings seldom explored. We show reliance sophisticated is not necessary, simple ...