59 citations · 238 across the 49 of their papers we have counts for
7 papers · 1 filter
This Face Does Not Exist ... But It Might Be Yours! Identity Leakage in Generative Models
Patrick Tinsley, Adam Czajka, Patrick Flynn
Generative adversarial networks (GANs) are able to generate high resolution photo-realistic images of objects that "do not exist." These synthetic images are rather difficult to de…
Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition
Priyanka Das, Joseph McGrath, Zhaoyuan Fang +20
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection…
Open Source Iris Recognition Hardware and Software with Presentation Attack Detection
Zhaoyuan Fang, Adam Czajka
This paper proposes the first known to us open source hardware and software iris recognition system with presentation attack detection (PAD), which can be easily assembled for abou…
Iris Presentation Attack Detection: Where Are We Now?
Aidan Boyd, Zhaoyuan Fang, Adam Czajka +1
As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount. This work presents an overvie…
Are Gabor Kernels Optimal for Iris Recognition?
Aidan Boyd, Adam Czajka, Kevin Bowyer
Gabor kernels are widely accepted as dominant filters for iris recognition. In this work we investigate, given the current interest in neural networks, if Gabor kernels are the onl…
Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch?
Aidan Boyd, Adam Czajka, Kevin Bowyer
Modern deep learning techniques can be employed to generate effective feature extractors for the task of iris recognition. The question arises: should we train such structures from…
Robust Iris Presentation Attack Detection Fusing 2D and 3D Information
Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
Diversity and unpredictability of artifacts potentially presented to an iris sensor calls for presentation attack detection methods that are agnostic to specificity of presentation…