Xucong Zhang
Papers
4
Total Citations
328
H-Index
3
About
Xucong Zhang is a computer vision researcher whose work spans gaze estimation, human-computer interaction, and the emerging application of augmented reality in surgical settings. He is perhaps best known for his foundational contributions to gaze estimation research, most notably the creation of ETH-XGaze, a large-scale dataset designed to benchmark gaze estimation under extreme head pose and gaze variation. This dataset addressed a critical gap in the field — the lack of a standardized, diverse benchmark — and has become a widely adopted reference point for the research community, accumulating nearly 300 citations since its release in 2020. By enabling fair cross-method comparison, Zhang's dataset work has meaningfully accelerated progress in applications ranging from robotics to human-computer interaction. More recently, Zhang has extended his expertise into surgical augmented reality, contributing to feasibility studies exploring real-time 3D anatomical overlays during minimally invasive thoracoscopic and robotic mitral valve repair surgeries. These interdisciplinary projects demonstrate his ability to translate core computer vision principles into high-stakes clinical environments. Across his career, Zhang exemplifies how foundational dataset contributions and applied visual computing can together push the boundaries of both academic research and real-world medical innovation.
Research Focus
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Top Papers
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