UEyes is a large eye-tracking-based dataset including 62 participants and 1,980 UI screenshots, covering four major UI types: webpage, desktop UI, mobile UI, and poster. Please cite the following paper: UEyes: Understanding Visual Saliency across User Interface Types https://dl.acm.org/doi/10.1145/3544548.3581096 Yue Jiang, Luis A. Leiva, Hamed Rezazadegan Tavakoli, Paul R. B. Houssel, Julia Kylmälä, and Antti Oulasvirta. 2023. UEyes: Understanding Visual Saliency across User Interface Types. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 285, 1–21. https://doi.org/10.1145/3544548.3581096

{"references": ["Yue Jiang, Luis A. Leiva, Hamed Rezazadegan Tavakoli, Paul R. B. Houssel, Julia Kylm\u00e4l\u00e4, and Antti Oulasvirta. 2023. UEyes: Understanding Visual Saliency across User Interface Types. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 285, 1\u201321. https://doi.org/10.1145/3544548.3581096"]}