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MPIIFaceGaze: It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation

We present the MPIIFaceGaze dataset which is based on the MPIIGaze dataset, with the additional human facial landmark annotation and the face regions are available. We added additional facial landmark and pupil center annotations for 37,667 face images. Facial landmarks annotations were conducted in a semi-automatic manner as running facial landmark detection method first and then checking by two human annotators. The pupil centers were annotated by two human annotators from scratch. For sake of privacy, we only released the face region and blocked the background in images.

More information can be found here.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License .

Download: Please download the full dataset here (940 Mb).

You can also download the normalized data from here, which includes the normalized face images as 448*448 pixels size and 2D gaze angle vectors. Please note that the data normalization procedure changed the gaze direction label so that you need to convert results based on this normalized data to the original camera space.

Contact: Andreas Bulling,

The data is only to be used for non-commercial scientific purposes. If you use this dataset in a scientific publication, please cite the following paper:

  1. MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

    MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

    Xucong Zhang, Yusuke Sugano, Mario Fritz, Andreas Bulling

    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(1), pp. 162-175, 2019.

    Abstract Links BibTeX Project

  1. It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation

    It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation

    Xucong Zhang, Yusuke Sugano, Mario Fritz, Andreas Bulling

    Proc. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2299-2308, 2017.

    Abstract Links BibTeX Project