FRGC-Morphs

FRGC-Morphs is a dataset of morphed faces selected from the publicly available FRGC dataset.

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Database Description

FRGC-Morphs is a dataset of morphed faces selected from the publicly available FRGC dataset (https://www.nist.gov/programs-projects/face-recognition-grand-challenge-frgc).
We created the database by selecting similar looking pairs of people, and made 3 types of morphs for each pair using the following morphing tools:

Instructions

This dataset is planned for vulnerability analysis experiments in the context of face recognition.
Therefore, it is intended to be used in conjunction with the original FRGC dataset.
The `copy_original_frgc.py` file included with this dataset helps with preparing the file structure so this folder may easily be used for such experiments.

    $ python copy_original_frgc.py /path/to/bonafide/frgc/folder

Once completed the directory's structure should be as given below:

+-- frgc
|   +-- morph_facemorpher
|   +-- morph_opencv
|   +-- morph_stylegan
|   +-- raw
|   +-- protocols
|   +-- copy_original_frgc.py
|   +-- frgc_selection.csv
|   +-- README.txt

Protocols

The vulnerability analysis can be conducted in two ways, using:

  • morphed images as references (`reverse-protocol`)
  • morphed images as probes (`scores-protocol`)

The protocols for both types of experiments are provided in the `protocols` folder, each of which contains the file lists of detailing the exact images used as references (`for_models.lst`) and as probes (`for_probes.lst`) for each morphing tool.

The data is *not* split into subsets, rather a single set is provided both as the development (`dev`) and evaluation set (`eval`) in order to be easily used by a toolkit such as bob (https://www.idiap.ch/software/bob).

References

Any publication (eg. conference paper, journal article, technical report, book chapter, etc) resulting from the usage of FRGC_Morphs must cite the following paper:

@article{Sarkar2020,
    title   = {Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks},
    author  = {Eklavya Sarkar and Pavel Korshunov and Laurent Colbois and S\'{e}bastien Marcel},
    year    = {2020},
    month   = oct,
    journal = {arXiv preprint},
    url     = {https://arxiv.org/abs/2012.05344}
}

Any publication (eg. conference paper, journal article, technical report, book chapter, etc) resulting from the usage of FRGC and subsequently FRGC_Morphs must also cite the following paper:

 P. J. Phillips, P. J. Flynn, T. Scruggs, K. W. Bowyer, Jin Chang, K. Hoffman, J. Marques, Jaesik Min, and W. Worek,
 Overview of the face recognition grand challenge.
 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), Vol. 1, pp. 947–954, 2005.