Name
Abstract | ||
|---|---|---|
Anti-spoofing attack detection is critical to guarantee the security of face-based authentication and facial analysis systems. Recently, a multi-modalface anti-spoofing dataset, CASIA-SURF, has been released with the goal of boosting research in this important topic. CASIA-SURF is the largest public data set for facial anti-spoofing attack detection in terms of both, diversity and modalities: it comprises 1,000 subjects and 21, 000 video samples. We organized a challenge around this novel resource to boost research in the subject. The Chalearn LAP multi-modal face anti-spoofing attack detection challenge attracted more than 300 teams for the development phase with a total of 13 teams qualifying for the final round. This paper presents an overview of the challenge, including its design, evaluation protocol and a summary of results. We analyze the top ranked solutions and draw conclusions derived from the competition. In addition we outline future work directions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CVPRW.2019.00202 | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
Field | DocType | ISSN |
Computer vision,Computer science,Artificial intelligence,Modal,Anti spoofing | Conference | 2160-7508 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
11 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ajian Liu | 1 | 14 | 4.19 |
| Jun Wan | 2 | 255 | 22.37 |
| Sergio Escalera | 3 | 1415 | 113.31 |
| Hugo Jair Escalante | 4 | 939 | 73.89 |
| Zichang Tan | 5 | 32 | 6.48 |
| Qi Yuan | 6 | 1 | 0.69 |
| Kai Wang | 7 | 1734 | 195.03 |
| chi lin | 8 | 50 | 4.81 |
| Guodong Guo | 9 | 2548 | 144.00 |
| Isabelle Guyon | 10 | 11033 | 1544.34 |
| Stan Z. Li | 11 | 8951 | 535.26 |