Gaze Target Detection

Gaze target detection aims to identify where a person is looking within an image or scene, a crucial task with applications in human-computer interaction and other fields. Recent research focuses on improving accuracy and efficiency, particularly by developing deep learning models that leverage multimodal data (e.g., head pose, body pose, depth maps, and scene context) and employing techniques like active learning to reduce reliance on large labeled datasets. These advancements are leading to more robust and privacy-preserving gaze estimation systems, with improved performance demonstrated across various benchmark datasets. The resulting improvements have significant implications for applications requiring accurate and efficient understanding of human visual attention.