The SWAX Benchmark

The Sense Wax Attack (SWAX) Database comprises images of real persons and their correponding realistic wax-made sculptures. The proposed benchmark seemed to be the only database containing both real and wax-modeled persons up to the publication date of the scientific paper. SWAX was designed to investigate the problem in which a face media is presented to a system that must determine whether it categorizes a bona fide (authentic) or a counterfeit (attack) sample.


The proposed SWAX dataset consists of genuine and counterfeit samples for all available subjects. As illustrated in the figures below (photos of real persons and wax dummies, respectively), the dataset contains labeled photographs of characters, celebrities and public figures, chosen based on a list of waxworks obtained from a famous chain of wax museums. More precisely, this work aims at investigating face spoofing detection in realistic scenarios, whither there is little control over the images acquisition. In contemplation of fair algorithm comparisons, we provide four protocols for developing and evaluating algorithms using the SWAX benchmark.


An illustration of bona-fide faces

SWAX is compiled from unrestrained online resources and consists of characters, celebrities and public figure images and videos to whom wax dummies have been sculpted into. The database contains 33 female and 22 male individuals. It consists of 1,812 images and 110 videos of 55 people/figures.  More precisely, each subject holds at least 20 authentic still images and a minimum of 10 counterfeit images. All motion and still pictures are manually captured under uncontrolled scenarios, formed by uncooperative individuals and distinct camera viewpoints.

An illustration of counterfeit faces

For development purposes, the proposed dataset encompasses a leave-one-out cross validation strategy in an attempt to escape unfairly algorithm biases and expose overfitting occurrences.

For more information on this dataset: