Spectrum-aware discriminative deep feature learning for multi-spectral face recognition

作者：

Highlights：

• Deep metric learning technique is first introduced into the multi-spectral face recognition task.

• The spectrum-aware embedding loss takes both the spectrum and class label information into consideration.

• The multi-spectral discriminant correlation loss fully exploits the useful correlation information in multi-spectral images.

• The proposed approach significantly outperforms state-of-the-art multi-spectral face recognition methods.

摘要

•Deep metric learning technique is first introduced into the multi-spectral face recognition task.•The spectrum-aware embedding loss takes both the spectrum and class label information into consideration.•The multi-spectral discriminant correlation loss fully exploits the useful correlation information in multi-spectral images.•The proposed approach significantly outperforms state-of-the-art multi-spectral face recognition methods.

论文关键词：Deep feature learning,Inter-spectrum correlation,Intra- and inter-spectrum discrimination,Multi-spectral face recognition

论文评审过程：Received 26 August 2019, Revised 22 June 2020, Accepted 6 September 2020, Available online 14 September 2020, Version of Record 22 September 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107632