3 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
Race Bias Analysis of Bona Fide Errors in face anti-spoofing
Latifah Abduh, Ioannis Ivrissimtzis
The study of bias in Machine Learning is receiving a lot of attention in recent years, however, few only papers deal explicitly with the problem of race bias in face anti-spoofing.…
Use of in-the-wild images for anomaly detection in face anti-spoofing
Latifah Abduh, Ioannis Ivrissimtzis
The traditional approach to face anti-spoofing sees it as a binary classification problem, and binary classifiers are trained and validated on specialized anti-spoofing databases.…
A study of the effect of the illumination model on the generation of synthetic training datasets
Xin Zhang, Ning Jia, Ioannis Ivrissimtzis
The use of computer generated images to train Deep Neural Networks is a viable alternative to real images when the latter are scarce or expensive. In this paper, we study how the i…
Watermark retrieval from 3D printed objects via synthetic data training
Xin Zhang, Ning Jia, Ioannis Ivrissimtzis
We present a deep neural network based method for the retrieval of watermarks from images of 3D printed objects. To deal with the variability of all possible 3D printing and image…
Watermark Retrieval from 3D Printed Objects via Convolutional Neural Networks
Xin Zhang, Qian Wang, Toby Breckon +1
We present a method for reading digital data embedded in planar 3D printed surfaces. The data are organised in binary arrays and embedded as surface textures in a way inspired by Q…