Human gaze provides valuable information on human focus and intentions, making it a
crucial area of research. Recently, deep learning has revolutionized appearance-based …

Facial video-based remote physiological measurement aims to estimate remote
photoplethysmography (rPPG) signals from human facial videos and then measure multiple …

Gaze estimator computes the gaze direction based on face images. Most existing gaze
estimation methods perform well under within-dataset settings, but can not generalize to …

Deep regression models typically learn in an end-to-end fashion without explicitly
emphasizing a regression-aware representation. Consequently, the learned representations …

Monocular 3D object detection poses a significant challenge due to the lack of depth
information in RGB images. Many existing methods strive to enhance the object depth …

Deep regression models typically learn in an end-to-end fashion and do not explicitly try to
learn a regression-aware representation. Their representations tend to be fragmented and …

Gaze estimation across domains has been explored recently because the training data are
usually collected under controlled conditions while the trained gaze estimators are used in …

The ability of gaze estimation models to generalize is often significantly hindered by various
factors unrelated to gaze, especially when the training dataset is limited. Current strategies …

The focus of Source-free Unsupervised Domain Adaptation (SFUDA) is to effectively transfer
a well-trained model from the source domain to an unlabelled target domain. During the …

Despite the recent development of learning-based gaze estimation methods, most methods
require one or more eye or face region crops as inputs and produce a gaze direction vector …