At the heart of affective computing lies the crucial task of decoding human emotions, a field
that expertly intertwines emotion identification with the nuances of sentiment analysis. This …

Although face recognition technology has been applied in many scenarios, it still suffers
from many types of presentation attacks, so face anti-spoofing (FAS) becomes a hot topic in …

Cross-spectral face recognition (CFR) refers to recognizing individuals using face images
stemming from different spectral bands, such as infrared versus visible. While CFR is …

Self-supervised contrastive learning (SCL) has emerged as a crucial technique for
unsupervised fine-grained feature extraction in the deep learning field. However, model …

In response to the escalating sophistication of cyber threats, traditional security measures
are proving insufficient, necessitating advanced solutions. The complexity of cyberattacks …

Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to explore the
cross-modal associations and learn modality-invariant representations without manual …

Near-Infrared and Visible light (NIR-VIS) face recognition methods have achieved
remarkable success in the fields of security surveillance, criminal investigation, and …

Data-driven intelligent diagnosis of insulation defects, based on partial discharge signal, is
an efficient strategy for evaluating the safety of gas-insulated switchgear (GIS). However, the …

Striving to match the person identities between visible (VIS) and near-infrared (NIR) images,
VIS-NIR reidentification (Re-ID) has attracted increasing attention due to its wide …

Near infrared-visible (NIR-VIS) heterogeneous face recognition aims to match face identities
in cross-modality settings, which has achieved significant development recently. The work …