11 citations · 25 across the 12 of their papers we have counts for
6 papers · 1 filter
SRTGAN: Triplet Loss based Generative Adversarial Network for Real-World Super-Resolution
Dhruv Patel, Abhinav Jain, Simran Bawkar +6
Many applications such as forensics, surveillance, satellite imaging, medical imaging, etc., demand High-Resolution (HR) images. However, obtaining an HR image is not always possib…
Time flies by: Analyzing the Impact of Face Ageing on the Recognition Performance with Synthetic Data
Marcel Grimmer, Haoyu Zhang, Raghavendra Ramachandra +2
The vast progress in synthetic image synthesis enables the generation of facial images in high resolution and photorealism. In biometric applications, the main motivation for using…
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
Marco Huber, Fadi Boutros, Anh Thi Luu +16
This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Con…
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
Ying Xu, Philipp Terhörst, Kiran Raja +1
In recent years, image and video manipulations with Deepfake have become a severe concern for security and society. Many detection models and datasets have been proposed to detect…
On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations
Philipp Terhörst, Florian Bierbaum, Marco Huber +4
A MasterFace is a face image that can successfully match against a large portion of the population. Since their generation does not require access to the information of the enrolle…
Analyzing Human Observer Ability in Morphing Attack Detection -- Where Do We Stand?
Sankini Rancha Godage, Frøy Løvåsdal, Sushma Venkatesh +3
Few studies have focused on examining how people recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS and offered morphing att…