Zero-shot learning via a specific rank-controlled semantic autoencoder

Yang Liu, Xinbo Gao, Jungong Han, Li Liu, Ling Shao

Abstract: Highlights•The proposed LSA model solves the domain shift problem, and considers the low-rank structure of the reconstruction data.•The proposed SRSA model can avoid simultaneously minimizing the variance of reconstruction data.•Comprehensive experiments on some datasets demonstrate the effectiveness of the proposed approaches.