Few-Shot Classification in Unseen Domains by Episodic Meta-Learning
Across Visual Domains
Few-Shot Classification in Unseen Domains by Episodic Meta-Learning
Across Visual Domains
Few-shot classification aims to carry out classification given only few labeled examples for the categories of interest. Though several approaches have been proposed, most existing few-shot learning (FSL) models assume that base and novel classes are drawn from the same data domain. When it comes to recognizing novel-class data in …