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

Eye gaze analysis is an important research problem in the field of Computer Vision and
Human-Computer Interaction. Even with notable progress in the last 10 years, automatic …

Abstract Appearance-based Gaze Estimation leverages deep neural networks to regress the
gaze direction from monocular images and achieve impressive performance. However, its …

In this paper, we present our method for neural face reenactment, called HyperReenact, that
aims to generate realistic talking head images of a source identity, driven by a target facial …

Human gaze is a crucial cue used in various applications such as human-robot interaction
and virtual reality. Recently, convolution neural network (CNN) approaches have made …

Recent work has proven the effectiveness of transformers in many computer vision tasks.
However, the performance of transformers in gaze estimation is still unexplored. In this …

Computer graphics has experienced a recent surge of data-centric approaches for
photorealistic and controllable content creation. StyleGAN in particular sets new standards …

Human gaze estimation plays a major role in many applications in human–computer
interaction and computer vision by identifying the users' point-of-interest. Revolutionary …

In this paper, we present EV-Eye, a first-of-its-kind large scale multimodal eye tracking
dataset aimed at inspiring research on high-frequency eye/gaze tracking. EV-Eye utilizes an …

Recent advances of deep learning-based approaches have achieved remarkable
performance on appearance-based gaze estimation. However, due to the shortage of target …