Appearance-based gaze estimation is believed to work well in real-world settings, but
existing datasets have been collected under controlled laboratory conditions and methods …

Learning-based methods are believed to work well for unconstrained gaze estimation, ie
gaze estimation from a monocular RGB camera without assumptions regarding user …

There is much interest in computer vision to utilize commodity hardware for gaze estimation.
A number of papers have shown that algorithms based on deep convolutional architectures …

Appearance-based gaze estimation is promising for unconstrained real-world settings, but
the significant variability in head pose and user-camera distance poses significant …

Background Eye-tracking technology for mobile devices has made significant progress.
However, owing to limited computing capacity and the complexity of context, the …

Gaze estimation methods have significantly matured in recent years, but the large number of
eye images required to train deep learning models poses significant privacy risks. In …

Gaze estimation using monocular cameras has significant commercial applicability, and
many studies have been undertaken on head pose-invariant and calibration-free gaze …

We propose a gaze estimation method not from eye observation but from head motion. This
proposed method is based on physiological studies about the eye-head coordination, and …

The real visual attention areas of students during the learning process are vital data. They
represent the students' visual concentration and provide strong support for the analysis of …

Latest gaze estimation methods require large-scale training data but their collection and
exchange pose significant privacy risks. We propose PrivatEyes-the first privacy-enhancing …