The SWAX Benchmark: Attacking Biometric Systems with Wax Figures
Not on the map. Why?
Abstract (arXiv)
A face spoofing attack occurs when an intruder attempts to impersonate someone who carries a gainful authentication clearance. It is a trending topic due to the increasing demand for biometric authentication on mobile devices, high-security areas, among others. This work introduces a new database named Sense Wax Attack dataset (SWAX), comprised of real human and wax figure images and videos that endorse the problem of face spoofing detection. The dataset consists of more than 1800 face images and 110 videos of 55 people/waxworks, arranged in training, validation and test sets with a large range in expression, illumination and pose variations. Experiments performed with baseline methods show that despite the progress in recent years, advanced spoofing methods are still vulnerable to high-quality violation attempts.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Oct 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
4 papers.
- 2021Deep Learning for Face Anti-Spoofing: A Surveycited by 65
- 2023Wild Face Anti-Spoofing Challenge 2023: Benchmark and Resultscited by 2
- 2022Face Presentation Attack Detectioncited by 0
- 2025Robust Face Liveness Detection for Biometric Authentication using Single Imagecited by 0
- 2025Robust Face Liveness Detection for Biometric Authentication using Single Image4 Nov 2025
- 2023Wild Face Anti-Spoofing Challenge 2023: Benchmark and Results12 Apr 2023
- 2022Face Presentation Attack Detection7 Dec 2022
- 2021Deep Learning for Face Anti-Spoofing: A Survey28 Jun 2021