First Competition on Presentation Attack Detection on ID Card
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866912413423501312 |
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| author | Tapia, Juan E. Damer, Naser Busch, Christoph Espin, Juan M. Barrachina, Javier Rocamora, Alvaro S. Ocvirk, Kristof Alessio, Leon Batagelj, Borut Patwardhan, Sushrut Ramachandra, Raghavendra Mudgalgundurao, Raghavendra Raja, Kiran Schulz, Daniel Aravena, Carlos |
| author_facet | Tapia, Juan E. Damer, Naser Busch, Christoph Espin, Juan M. Barrachina, Javier Rocamora, Alvaro S. Ocvirk, Kristof Alessio, Leon Batagelj, Borut Patwardhan, Sushrut Ramachandra, Raghavendra Mudgalgundurao, Raghavendra Raja, Kiran Schulz, Daniel Aravena, Carlos |
| contents | This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competition presented an independent assessment of current state-of-the-art algorithms. Today, no independent evaluation on cross-dataset is available; therefore, this work determined the state-of-the-art on ID cards. To reach this goal, a sequestered test set and baseline algorithms were used to evaluate and compare all the proposals. The sequestered test dataset contains ID cards from four different countries. In summary, a team that chose to be "Anonymous" reached the best average ranking results of 74.80%, followed very closely by the "IDVC" team with 77.65%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00372 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | First Competition on Presentation Attack Detection on ID Card Tapia, Juan E. Damer, Naser Busch, Christoph Espin, Juan M. Barrachina, Javier Rocamora, Alvaro S. Ocvirk, Kristof Alessio, Leon Batagelj, Borut Patwardhan, Sushrut Ramachandra, Raghavendra Mudgalgundurao, Raghavendra Raja, Kiran Schulz, Daniel Aravena, Carlos Computer Vision and Pattern Recognition This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competition presented an independent assessment of current state-of-the-art algorithms. Today, no independent evaluation on cross-dataset is available; therefore, this work determined the state-of-the-art on ID cards. To reach this goal, a sequestered test set and baseline algorithms were used to evaluate and compare all the proposals. The sequestered test dataset contains ID cards from four different countries. In summary, a team that chose to be "Anonymous" reached the best average ranking results of 74.80%, followed very closely by the "IDVC" team with 77.65%. |
| title | First Competition on Presentation Attack Detection on ID Card |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2409.00372 |