20 citations · 45 across the 24 of their papers we have counts for
25 papers
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
Meiling Fang, Marco Huber, Julian Fierrez +21
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 Internation…
Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Edition
Patrick Tinsley, Sandip Purnapatra, Mahsa Mitcheff +18
This paper describes the results of the 2023 edition of the ''LivDet'' series of iris presentation attack detection (PAD) competitions. New elements in this fifth competition inclu…
Liveness Detection Competition -- Noncontact-based Fingerprint Algorithms and Systems (LivDet-2023 Noncontact Fingerprint)
Sandip Purnapatra, Humaira Rezaie, Bhavin Jawade +19
Liveness Detection (LivDet) is an international competition series open to academia and industry with the objec-tive to assess and report state-of-the-art in Presentation Attack De…
Face Presentation Attack Detection by Excavating Causal Clues and Adapting Embedding Statistics
Meiling Fang, Naser Damer
Recent face presentation attack detection (PAD) leverages domain adaptation (DA) and domain generalization (DG) techniques to address performance degradation on unknown domains. Ho…
ExFaceGAN: Exploring Identity Directions in GAN's Learned Latent Space for Synthetic Identity Generation
Fadi Boutros, Marcel Klemt, Meiling Fang +2
Deep generative models have recently presented impressive results in generating realistic face images of random synthetic identities. To generate multiple samples of a certain synt…
SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Data
Meiling Fang, Marco Huber, Naser Damer
Recently, significant progress has been made in face presentation attack detection (PAD), which aims to secure face recognition systems against presentation attacks, owing to the a…
Are Explainability Tools Gender Biased? A Case Study on Face Presentation Attack Detection
Marco Huber, Meiling Fang, Fadi Boutros +1
Face recognition (FR) systems continue to spread in our daily lives with an increasing demand for higher explainability and interpretability of FR systems that are mainly based on…
MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders
Naser Damer, Meiling Fang, Patrick Siebke +3
Investigating new methods of creating face morphing attacks is essential to foresee novel attacks and help mitigate them. Creating morphing attacks is commonly either performed on…
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…
Fairness in Face Presentation Attack Detection
Meiling Fang, Wufei Yang, Arjan Kuijper +2
Face recognition (FR) algorithms have been proven to exhibit discriminatory behaviors against certain demographic and non-demographic groups, raising ethical and legal concerns reg…
Unsupervised Face Morphing Attack Detection via Self-paced Anomaly Detection
Meiling Fang, Fadi Boutros, Naser Damer
The supervised-learning-based morphing attack detection (MAD) solutions achieve outstanding success in dealing with attacks from known morphing techniques and known data sources. H…
Intra and Cross-spectrum Iris Presentation Attack Detection in the NIR and Visible Domains
Meiling Fang, Fadi Boutros, Naser Damer
Iris Presentation Attack Detection (PAD) is essential to secure iris recognition systems. Recent iris PAD solutions achieved good performance by leveraging deep learning techniques…
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…
CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
Fadi Boutros, Meiling Fang, Marcel Klemt +2
The quality of face images significantly influences the performance of underlying face recognition algorithms. Face image quality assessment (FIQA) estimates the utility of the cap…
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…
MixFaceNets: Extremely Efficient Face Recognition Networks
Fadi Boutros, Naser Damer, Meiling Fang +2
In this paper, we present a set of extremely efficient and high throughput models for accurate face verification, MixFaceNets which are inspired by Mixed Depthwise Convolutional Ke…
Iris Presentation Attack Detection by Attention-based and Deep Pixel-wise Binary Supervision Network
Meiling Fang, Naser Damer, Fadi Boutros +2
Iris presentation attack detection (PAD) plays a vital role in iris recognition systems. Most existing CNN-based iris PAD solutions 1) perform only binary label supervision during…
Masked Face Recognition: Human vs. Machine
Naser Damer, Fadi Boutros, Marius Süßmilch +3
The recent COVID-19 pandemic has increased the focus on hygienic and contactless identity verification methods. However, the pandemic led to the wide use of face masks, essential t…
Real Masks and Spoof Faces: On the Masked Face Presentation Attack Detection
Meiling Fang, Naser Damer, Florian Kirchbuchner +1
Face masks have become one of the main methods for reducing the transmission of COVID-19. This makes face recognition (FR) a challenging task because masks hide several discriminat…
Micro Stripes Analyses for Iris Presentation Attack Detection
Meiling Fang, Naser Damer, Florian Kirchbuchner +1
Iris recognition systems are vulnerable to the presentation attacks, such as textured contact lenses or printed images. In this paper, we propose a lightweight framework to detect…
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…