Heterogeneous face recognition (HFR) aims at matching face images across different
domains. It is challenging due to the severe domain discrepancies and overfitting caused by …

Heterogeneous Face Recognition (HFR) refers to matching face images captured in different
domains, such as thermal to visible images (VIS), sketches to visible images, near-infrared …

Abstract Heterogeneous Face Recognition (HFR) is a challenging issue because of the
large domain discrepancy and a lack of heterogeneous data. This paper considers HFR as a …

Abstract Heterogeneous Face Recognition (HFR) is a challenging task due to large modality
discrepancy as well as insufficient training images in certain modalities. In this paper, we …

Heterogeneous face recognition (HFR) refers to matching cross-domain faces and plays a
crucial role in public security. Nevertheless, HFR is confronted with challenges from large …

The large modality gap between faces captured in different spectra makes heterogeneous
face recognition (HFR) a challenging problem. In this paper, we present a coupled …

Heterogeneous face recognition (HFR) is a challenging problem in face recognition and
subject to large textural and spatial structure differences of face images. Different from …

Heterogeneous Face Recognition (HFR) is a task that matches faces across two different
domains such as visible light (VIS), near-infrared (NIR), or the sketch domain. Due to the …

Heterogeneous face recognition (HFR) is the process of matching face images captured
from different sources. HFR plays an important role in security scenarios. However, HFR …

Heterogeneous face recognition (HFR) is still a challenging problem in computer vision
community due to large appearance difference between near infrared (NIR) and visible light …