4 citations · 8 across the 9 of their papers we have counts for
12 papers
Unsupervised Face Recognition using Unlabeled Synthetic Data
Fadi Boutros, Marcel Klemt, Meiling Fang +2
Over the past years, the main research innovations in face recognition focused on training deep neural networks on large-scale identity-labeled datasets using variations of multi-c…
Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors
Naser Damer, César Augusto Fontanillo López, Meiling Fang +3
The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?". Towards that, this work introd…
Partial Attack Supervision and Regional Weighted Inference for Masked Face Presentation Attack Detection
Meiling Fang, Fadi Boutros, Arjan Kuijper +1
Wearing a mask has proven to be one of the most effective ways to prevent the transmission of SARS-CoV-2 coronavirus. However, wearing a mask poses challenges for different face re…
Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection
Meiling Fang, Naser Damer, Florian Kirchbuchner +1
With the increased deployment of face recognition systems in our daily lives, face presentation attack detection (PAD) is attracting much attention and playing a key role in securi…
PW-MAD: Pixel-wise Supervision for Generalized Face Morphing Attack Detection
Naser Damer, Noemie Spiller, Meiling Fang +3
A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks. Va…
ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation
Naser Damer, Kiran Raja, Marius Süßmilch +6
Face morphing attacks aim at creating face images that are verifiable to be the face of multiple identities, which can lead to building faulty identity links in operations like bor…