ID-Softmax: A Softmax-like Loss for ID Face Recognition

Yan Kong, Fuzhang Wu, Feiyue Huang, Yanjun Wu

2019

Abstract

The face recognition between photos from identification documents (ID, Citizen Card or Passport Card) and daily photos, which is named FRBID(Zhang et al., 2017), is widely used in real world scenarios. However, traditional Softmax loss of deep CNN usually lacks the power of discrimination for FRBID. To address this problem, in this paper, we first revisit recent progress of face recognition losses, and give the theoretical and experimental analysis on the reason why Softmax-like losses work badly on ID-daily face recognition. Then we propose an novel approach named ID-Softmax, which use ID face features as class ’agent’ to guide the deep CNNs to learn highly discriminative features between ID photos and daily photos. In order to promote the ID-daily face recognition, we collect a large dataset ID74K, which includes 74,187 identities with corresponding ID photos and daily photos. To test our approach, we evaluate the feature distribution and face verification performance on dataset ID74K. In experiments, we achieve the best performance when comparing with other state-of-the-art methods, which verifies the effectiveness of the proposed ID-Softmax loss.

Paper Citation

in Harvard Style

Kong Y., Wu F., Huang F. and Wu Y. (2019). ID-Softmax: A Softmax-like Loss for ID Face Recognition. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 412-419. DOI: 10.5220/0007370904120419

in Bibtex Style

@conference{visapp19,
author={Yan Kong and Fuzhang Wu and Feiyue Huang and Yanjun Wu},
title={ID-Softmax: A Softmax-like Loss for ID Face Recognition},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={412-419},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007370904120419},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - ID-Softmax: A Softmax-like Loss for ID Face Recognition
SN - 978-989-758-354-4
AU - Kong Y.
AU - Wu F.
AU - Huang F.
AU - Wu Y.
PY - 2019
SP - 412
EP - 419
DO - 10.5220/0007370904120419
PB - SciTePress