Awesome

SYN-MAD-2022

This is the repository for the IJCB-SYN-MAD-2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data. The competition was held at the International Joint Conference on Biometrics 2022.

The final results of the competition will be presented in a summary paper at IJCB 2022. The link to the paper will be added soon.

Competition Training Data

The synthetic training data that the competitors were allowed to use for training the morphing detectors was limited to the SMDD dataset. This can be requested here. In addition, we also provide two files containing the bounding boxes and facial landmark points:

• Bounding box for morphed images of SMDD
• Bounding box for bona fide images of SMDD

Bounding Box / Landmarks

The files contain in each line a sample, e.g.:

 ./m15k_t/morphed_img000184_img282038.png 43 197 41 240 97 123 161 123 133 156 95 182 158 183

The values in each row are structured as follows:

/path/referene_1.jpg bb_x1 bb_x2 bb_y1 bb_y2 left_eye_x left_eye_y right_eye_x right_eye_y nose_x nose_y mouth_left_x mouth_left_y mouth_right_x mouth_right_y 

were x1, x2, y1 and y2 are the bounding boxs points. And all others number refer to the respective coordinates of the face landmarks (left eye, right eye, nose, mouth left, mouth right).

Competition Testing Data

For the evaluation of the submissions a new benchmark, MAD22 has been created by the organizers of the competittion. The benchmark is based on the Face Research Lab London dataset (FRLL). The created benchmark contains 4483 morphed face images and 204 bona fide images from the FRLL dataset and five different morphing approaches (three landmark-based, two GAN-based) has been used to create the dataset. For more details on the benchmark, we refer to the competition summary paper.

The MAD22 benchmark can be requested here. Please share your name, affiliation, and official email in the request form. The bounding boxes and landmarks are included and presented in the same way as described above.

If you use the MAD22 benchmark, please cite:

@misc{https://doi.org/10.48550/arxiv.2208.07337,
  doi = {10.48550/ARXIV.2208.07337},
  
  url = {https://arxiv.org/abs/2208.07337},
  
  author = {Huber, Marco and Boutros, Fadi and Luu, Anh Thi and Raja, Kiran and Ramachandra, Raghavendra and Damer, Naser and Neto, Pedro C. and Gonçalves, Tiago and Sequeira, Ana F. and Cardoso, Jaime S. and Tremoço, João and Lourenço, Miguel and Serra, Sergio and Cermeño, Eduardo and Ivanovska, Marija and Batagelj, Borut and Kronovšek, Andrej and Peer, Peter and Štruc, Vitomir},
  
  keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data},
  
  publisher = {arXiv},
  
  year = {2022},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}