activity
20172020
most citedFederated Face Presentation Attack Detection

5 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2020

Open-set Adversarial Defense

Rui Shao, Pramuditha Perera, Pong C. Yuen +1

Open-set recognition and adversarial defense study two key aspects of deep learning that are vital for real-world deployment. The objective of open-set recognition is to identify s…

cs.CV2020

Anomaly Detection-Based Unknown Face Presentation Attack Detection

Yashasvi Baweja, Poojan Oza, Pramuditha Perera +1

Anomaly detection-based spoof attack detection is a recent development in face Presentation Attack Detection (fPAD), where a spoof detector is learned using only non-attacked image…

cs.CV2020

Quickest Intruder Detection for Multiple User Active Authentication

Pramuditha Perera, Julian Fierrez, Vishal M. Patel

In this paper, we investigate how to detect intruders with low latency for Active Authentication (AA) systems with multiple-users. We extend the Quickest Change Detection (QCD) fra…

cs.CV20205 cited

Federated Face Presentation Attack Detection

Rui Shao, Pramuditha Perera, Pong C. Yuen +1

Face presentation attack detection (fPAD) plays a critical role in the modern face recognition pipeline. A face presentation attack detection model with good generalization can be…

cs.CV2019

Deep Transfer Learning for Multiple Class Novelty Detection

Pramuditha Perera, Vishal M. Patel

We propose a transfer learning-based solution for the problem of multiple class novelty detection. In particular, we propose an end-to-end deep-learning based approach in which we…

cs.CV2017

In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

Pramuditha Perera, Mahdi Abavisani, Vishal M. Patel

In unsupervised image-to-image translation, the goal is to learn the mapping between an input image and an output image using a set of unpaired training images. In this paper, we p…