Style transformed synthetic images for real world gaze estimation by using residual neural network with embedded personal identities

Author:

Wang QuanORCID,Wang Hui,Dang Ruo-Chen,Zhu Guang-Pu,Pi Hai-Feng,Shic Frederick,Hu Bing-liang

Funder

xi’an institute of optics and precision mechanics

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference37 articles.

1. Majaranta P, Bulling A (2014) Eye tracking and eye-based human–computer interaction. Springer, Berlin, pp 39–65

2. Sugano Y, Zhang X, Bulling A (2016) Aggregaze: Collective estimation of audience attention on public displays. In: Symposium on user interface software & technology

3. Ali A, Kim Y-G (2020) Deep fusion for 3d gaze estimation from natural face images using multi-stream cnns. IEEE Access 8:69212–69221. https://doi.org/10.1109/ACCESS.2020.2986815

4. Peréz A, Córdoba ML, Garcia A, Méndez R, Munoz M, Pedraza JL, Sanchez F (2003) A precise eye-gaze detection and tracking system

5. Young D, Tunley H, Samuels R (1995) Specialised hough transform and active contour methods for real-time eye tracking. University of Sussex, Cognitive and Computing Science, Technical Report 386

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