We present SpeakingFaces as a publicly-available large-scale multimodal dataset
developed to support machine learning research in contexts that utilize a combination of …

Person recognition at a distance entails recognizing the identity of an individual appearing
in images or videos collected by long-range imaging systems such as drones or surveillance …

This paper presents a novel approach, called Prototype-based Self-Distillation (ProS), for
unsupervised face representation learning. The existing supervised methods heavily rely on …

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 …

Face detection and subsequent localization of facial landmarks are the primary steps in
many face applications. Numerous algorithms and benchmark datasets have been …

While systems based on deep neural networks have produced remarkable performance on
many tasks such as face/object detection and recognition, they also require large amounts of …

The thermal-to-visible (T2V) face translation task is essential for enabling face verification in
low-light or dark conditions by converting thermal infrared faces into their visible …

Modern-day surveillance systems perform person recognition using deep learning-based
face verification networks. Most state-of-the-art facial verification systems are trained using …

Near-InfraRed and VISual (NIR-VIS) face matching, as one of the most representative tasks
in Heterogeneous Face Recognition (HFR), aims at retrieving a face image across different …

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 …