Thermal face imagery, which captures the naturally emitted heat from the face, is limited in
availability compared to face imagery in the visible spectrum. To help address this scarcity of …

There has been increasing interest in face recognition in the thermal infrared spectrum. A
critical step in this process is face landmark detection. However, landmark detection in the …

In recent years, visible-spectrum face verification systems have been shown to match the
performance of experienced forensic examiners. However, such systems are ineffective in …

Facial landmark detection is a cornerstone in many facial analysis tasks such as face
recognition, drowsiness detection, and facial expression recognition. Numerous …

A large number of algorithms for processing faces in regular photographs and videos has
been published in recent years, making this field one of the most active research areas in …

Visible face recognition systems achieve nearly perfect recognition accuracies using deep
learning. However, in lack of light, these systems perform poorly. A way to deal with this …

Facial thermography is one of the most popular research areas in infrared thermal imaging,
with diverse applications in medical, surveillance, and environmental monitoring. However …

Existing thermal-to-visible face verification approaches expect the thermal and visible face
images to be of similar resolution. This is unlikely in real-world long-range surveillance …

We present a neural network to jointly consider facial landmark detection and emotion
recognition for thermal face images. The first part of this network is based on the U-Net …

Thermal-to-visible face verification is a challenging problem due to the large domain
discrepancy between the modalities. Existing approaches either attempt to synthesize …