Gaze Prediction

Gaze prediction, the task of estimating where a person is looking, is a rapidly evolving field with applications in human-computer interaction, virtual reality, and driver monitoring. Current research focuses on improving accuracy and efficiency using various deep learning architectures, including transformers, convolutional neural networks, and hybrid models that incorporate multimodal data (e.g., EEG, head pose, scene context). These advancements are driven by the need for robust and reliable gaze estimation in diverse and challenging environments, ultimately impacting fields requiring a deeper understanding of human attention and intention.