Search Results for author: Naser Damer

Found 87 papers, 46 papers with code

FRoundation: Are Foundation Models Ready for Face Recognition?

no code implementations31 Oct 2024 Tahar Chettaoui, Naser Damer, Fadi Boutros

Even with access to large-scale face recognition training datasets, fine-tuned foundation models perform comparably to models trained from scratch, but with lower training computational costs and without relying on the assumption of extensive data availability.

Face Recognition

A Survey on Drowsiness Detection -- Modern Applications and Methods

no code implementations23 Aug 2024 Biying Fu, Fadi Boutros, Chin-Teng Lin, Naser Damer

By examining the multifaceted implications of drowsiness, this work contributes to a holistic understanding of its impact and the crucial role of accurate and real-time detection techniques in enhancing safety and performance.

Model Compression Survey

Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain

no code implementations16 Jul 2024 Marco Huber, Naser Damer

In this work, we take a step forward and investigate explainable face recognition in the unexplored frequency domain.

Face Recognition

AdaDistill: Adaptive Knowledge Distillation for Deep Face Recognition

1 code implementation1 Jul 2024 Fadi Boutros, Vitomir Štruc, Naser Damer

Knowledge distillation (KD) aims at improving the performance of a compact student model by distilling the knowledge from a high-performing teacher model.

Face Recognition Knowledge Distillation

GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes

1 code implementation18 Apr 2024 Jan Niklas Kolf, Naser Damer, Fadi Boutros

We propose in this work a novel approach to assess the quality of face images based on inspecting the required changes in the pre-trained FR model weights to minimize differences between testing samples and the distribution of the FR training dataset.

Face Image Quality Face Image Quality Assessment +1

AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation

1 code implementation15 Apr 2024 Žiga Babnik, Fadi Boutros, Naser Damer, Peter Peer, Vitomir Štruc

To address this problem, we present in this paper a novel knowledge distillation approach, termed AI-KD that can extend on any existing FIQA technique, improving its robustness to alignment variations and, in turn, performance with different alignment procedures.

Face Alignment Face Image Quality +3

IEEE BigData 2023 Keystroke Verification Challenge (KVC)

1 code implementation29 Jan 2024 Giuseppe Stragapede, Ruben Vera-Rodriguez, Ruben Tolosana, Aythami Morales, Ivan DeAndres-Tame, Naser Damer, Julian Fierrez, Javier-Ortega Garcia, Nahuel Gonzalez, Andrei Shadrikov, Dmitrii Gordin, Leon Schmitt, Daniel Wimmer, Christoph Grossmann, Joerdis Krieger, Florian Heinz, Ron Krestel, Christoffer Mayer, Simon Haberl, Helena Gschrey, Yosuke Yamagishi, Sanjay Saha, Sanka Rasnayaka, Sandareka Wickramanayake, Terence Sim, Weronika Gutfeter, Adam Baran, Mateusz Krzyszton, Przemyslaw Jaskola

Several neural architectures were proposed by the participants, leading to global Equal Error Rates (EERs) as low as 3. 33% and 3. 61% achieved by the best team respectively in the desktop and mobile scenario, outperforming the current state of the art biometric verification performance for KD.

Model Compression Techniques in Biometrics Applications: A Survey

1 code implementation18 Jan 2024 Eduarda Caldeira, Pedro C. Neto, Marco Huber, Naser Damer, Ana F. Sequeira

The development of deep learning algorithms has extensively empowered humanity's task automatization capacity.

Fairness Knowledge Distillation +3

Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-adaption and Few-Shot Learning

no code implementations20 Nov 2023 Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

In previous works, a mobile application was developed using an unmodified commercial off-the-shelf smartphone to recognize whole-body exercises.

Domain Adaptation Few-Shot Learning

Keystroke Verification Challenge (KVC): Biometric and Fairness Benchmark Evaluation

no code implementations10 Nov 2023 Giuseppe Stragapede, Ruben Vera-Rodriguez, Ruben Tolosana, Aythami Morales, Naser Damer, Julian Fierrez, Javier Ortega-Garcia

Analyzing keystroke dynamics (KD) for biometric verification has several advantages: it is among the most discriminative behavioral traits; keyboards are among the most common human-computer interfaces, being the primary means for users to enter textual data; its acquisition does not require additional hardware, and its processing is relatively lightweight; and it allows for transparently recognizing subjects.

Fairness

Bias and Diversity in Synthetic-based Face Recognition

no code implementations7 Nov 2023 Marco Huber, Anh Thi Luu, Fadi Boutros, Arjan Kuijper, Naser Damer

In this work, we investigate how the diversity of synthetic face recognition datasets compares to authentic datasets, and how the distribution of the training data of the generative models affects the distribution of the synthetic data.

Attribute Diversity +1

Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Edition

no code implementations6 Oct 2023 Patrick Tinsley, Sandip Purnapatra, Mahsa Mitcheff, Aidan Boyd, Colton Crum, Kevin Bowyer, Patrick Flynn, Stephanie Schuckers, Adam Czajka, Meiling Fang, Naser Damer, Xingyu Liu, Caiyong Wang, Xianyun Sun, Zhaohua Chang, Xinyue Li, Guangzhe Zhao, Juan Tapia, Christoph Busch, Carlos Aravena, Daniel Schulz

New elements in this fifth competition include (1) GAN-generated iris images as a category of presentation attack instruments (PAI), and (2) an evaluation of human accuracy at detecting PAI as a reference benchmark.

Liveness Detection Competition -- Noncontact-based Fingerprint Algorithms and Systems (LivDet-2023 Noncontact Fingerprint)

no code implementations1 Oct 2023 Sandip Purnapatra, Humaira Rezaie, Bhavin Jawade, Yu Liu, Yue Pan, Luke Brosell, Mst Rumana Sumi, Lambert Igene, Alden Dimarco, Srirangaraj Setlur, Soumyabrata Dey, Stephanie Schuckers, Marco Huber, Jan Niklas Kolf, Meiling Fang, Naser Damer, Banafsheh Adami, Raul Chitic, Karsten Seelert, Vishesh Mistry, Rahul Parthe, Umit Kacar

The competition serves as an important benchmark in noncontact-based fingerprint PAD, offering (a) independent assessment of the state-of-the-art in noncontact-based fingerprint PAD for algorithms and systems, and (b) common evaluation protocol, which includes finger photos of a variety of Presentation Attack Instruments (PAIs) and live fingers to the biometric research community (c) provides standard algorithm and system evaluation protocols, along with the comparative analysis of state-of-the-art algorithms from academia and industry with both old and new android smartphones.

IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models

1 code implementation9 Aug 2023 Fadi Boutros, Jonas Henry Grebe, Arjan Kuijper, Naser Damer

The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.

Ranked #2 on Synthetic Face Recognition on AgeDB-30 (Accuracy metric)

Synthetic Face Recognition

EFaR 2023: Efficient Face Recognition Competition

1 code implementation8 Aug 2023 Jan Niklas Kolf, Fadi Boutros, Jurek Elliesen, Markus Theuerkauf, Naser Damer, Mohamad Alansari, Oussama Abdul Hay, Sara Alansari, Sajid Javed, Naoufel Werghi, Klemen Grm, Vitomir Štruc, Fernando Alonso-Fernandez, Kevin Hernandez Diaz, Josef Bigun, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Ketan Kotwal, Sébastien Marcel, Iurii Medvedev, Bo Jin, Diogo Nunes, Ahmad Hassanpour, Pankaj Khatiwada, Aafan Ahmad Toor, Bian Yang

To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size.

Lightweight Face Recognition Quantization

ExFaceGAN: Exploring Identity Directions in GAN's Learned Latent Space for Synthetic Identity Generation

1 code implementation11 Jul 2023 Fadi Boutros, Marcel Klemt, Meiling Fang, Arjan Kuijper, Naser Damer

To generate multiple samples of a certain synthetic identity, previous works proposed to disentangle the latent space of GANs by incorporating additional supervision or regularization, enabling the manipulation of certain attributes.

Attribute Face Recognition

Optimization-Based Improvement of Face Image Quality Assessment Techniques

1 code implementation24 May 2023 Žiga Babnik, Naser Damer, Vitomir Štruc

To help improve the performance and stability of FR systems in such unconstrained settings, face image quality assessment (FIQA) techniques try to infer sample-quality information from the input face images that can aid with the recognition process.

Face Image Quality Face Image Quality Assessment +1

Synthetic Data for Face Recognition: Current State and Future Prospects

no code implementations1 May 2023 Fadi Boutros, Vitomir Struc, Julian Fierrez, Naser Damer

Over the past years, deep learning capabilities and the availability of large-scale training datasets advanced rapidly, leading to breakthroughs in face recognition accuracy.

Face Recognition

Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition

2 code implementations30 Apr 2023 Jan Niklas Kolf, Tim Rieber, Jurek Elliesen, Fadi Boutros, Arjan Kuijper, Naser Damer

We empirically proved that our IDnet synthetic images are of higher identity discrimination in comparison to the conventional two-player GAN, while maintaining a realistic intra-identity variation.

Generative Adversarial Network Synthetic Face Recognition

Are Explainability Tools Gender Biased? A Case Study on Face Presentation Attack Detection

no code implementations26 Apr 2023 Marco Huber, Meiling Fang, Fadi Boutros, Naser Damer

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 deep learning.

Face Presentation Attack Detection Face Recognition

Efficient Explainable Face Verification based on Similarity Score Argument Backpropagation

1 code implementation26 Apr 2023 Marco Huber, Anh Thi Luu, Philipp Terhörst, Naser Damer

Explainable Face Recognition is gaining growing attention as the use of the technology is gaining ground in security-critical applications.

Face Recognition Face Verification

Multispectral Imaging for Differential Face Morphing Attack Detection: A Preliminary Study

no code implementations7 Apr 2023 Raghavendra Ramachandra, Sushma Venkatesh, Naser Damer, Narayan Vetrekar, Rajendra Gad

The D-MAD methods are based on using two facial images that are captured from the ePassport (also called the reference image) and the trusted device (for example, Automatic Border Control (ABC) gates) to detect whether the face image presented in ePassport is morphed.

Face Morphing Attack Detection

SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Data

2 code implementations5 Mar 2023 Meiling Fang, Marco Huber, Naser Damer

To target these legal and technical challenges, this work presents the first synthetic-based face PAD dataset, named SynthASpoof, as a large-scale PAD development dataset.

Diversity Domain Generalization +2

IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Model

1 code implementation ICCV 2023 Fadi Boutros, Jonas Henry Grebe, Arjan Kuijper, Naser Damer

The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.

Face Recognition

Periocular Biometrics: A Modality for Unconstrained Scenarios

no code implementations28 Dec 2022 Fernando Alonso-Fernandez, Josef Bigun, Julian Fierrez, Naser Damer, Hugo Proença, Arun Ross

Periocular refers to the externally visible region of the face that surrounds the eye socket.

Fairness in Face Presentation Attack Detection

2 code implementations19 Sep 2022 Meiling Fang, Wufei Yang, Arjan Kuijper, Vitomir Struc, Naser Damer

Face recognition (FR) algorithms have been proven to exhibit discriminatory behaviors against certain demographic and non-demographic groups, raising ethical and legal concerns regarding their deployment in real-world scenarios.

Attribute Data Augmentation +3

Towards Explaining Demographic Bias through the Eyes of Face Recognition Models

1 code implementation29 Aug 2022 Biying Fu, Naser Damer

To improve the trustfulness of such ML decision systems, it is crucial to be aware of the inherent biases in these solutions and to make them more transparent to the public and developers.

Decision Making Face Recognition +1

Unsupervised Face Morphing Attack Detection via Self-paced Anomaly Detection

1 code implementation11 Aug 2022 Meiling Fang, Fadi Boutros, Naser Damer

However, given variations in the morphing attacks, the performance of supervised MAD solutions drops significantly due to the insufficient diversity and quantity of the existing MAD datasets.

Anomaly Detection Face Morphing Attack Detection +1

SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data

1 code implementation21 Jun 2022 Fadi Boutros, Marco Huber, Patrick Siebke, Tim Rieber, Naser Damer

The reported evaluation results on five authentic face benchmarks demonstrated that the privacy-friendly synthetic dataset has high potential to be used for training face recognition models, achieving, for example, a verification accuracy of 91. 87\% on LFW using multi-class classification and 99. 13\% using the combined learning strategy.

Face Recognition Generative Adversarial Network +2

QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization

1 code implementation21 Jun 2022 Fadi Boutros, Naser Damer, Arjan Kuijper

Deep learning-based face recognition models follow the common trend in deep neural networks by utilizing full-precision floating-point networks with high computational costs.

Lightweight Face Recognition Quantization

Intra and Cross-spectrum Iris Presentation Attack Detection in the NIR and Visible Domains

no code implementations5 May 2022 Meiling Fang, Fadi Boutros, Naser Damer

Extensive experiments are performed on six NIR and one visible-light iris databases to show the effectiveness and robustness of proposed A-PBS methods.

Iris Recognition

On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations

no code implementations23 Mar 2022 Philipp Terhörst, Florian Bierbaum, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper

However, previous works followed evaluation settings consisting of older recognition models, limited cross-dataset and cross-model evaluations, and the use of low-scale testing data.

Face Recognition Fairness

Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors

1 code implementation13 Mar 2022 Naser Damer, César Augusto Fontanillo López, Meiling Fang, Noémie Spiller, Minh Vu Pham, Fadi Boutros

The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?".

CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

1 code implementation CVPR 2023 Fadi Boutros, Meiling Fang, Marcel Klemt, Biying Fu, Naser Damer

Based on that, our proposed CR-FIQA uses this paradigm to estimate the face image quality of a sample by predicting its relative classifiability.

Face Image Quality Face Image Quality Assessment +1

Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

1 code implementation9 Dec 2021 Biying Fu, Naser Damer

To avoid the low discrimination between the general spatial activation mapping of low and high-quality images in FR models, we build our explainability tools in a higher derivative space by analyzing the variation of the FR activation maps of image sets with different quality decisions.

Face Image Quality Face Image Quality Assessment +1

QMagFace: Simple and Accurate Quality-Aware Face Recognition

1 code implementation26 Nov 2021 Philipp Terhörst, Malte Ihlefeld, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper

These variabilities can be measured in terms of face image quality which is defined over the utility of a sample for recognition.

Face Image Quality Face Recognition +1

Partial Attack Supervision and Regional Weighted Inference for Masked Face Presentation Attack Detection

no code implementations8 Nov 2021 Meiling Fang, Fadi Boutros, Arjan Kuijper, Naser Damer

Our proposed method outperforms established PAD methods in the CRMA database by reducing the mentioned shortcomings when facing masked faces.

Face Presentation Attack Detection Face Recognition

FocusFace: Multi-task Contrastive Learning for Masked Face Recognition

1 code implementation28 Oct 2021 Pedro C. Neto, Fadi Boutros, João Ribeiro Pinto, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso

The proposed architecture is designed to be trained from scratch or to work on top of state-of-the-art face recognition methods without sacrificing the capabilities of a existing models in conventional face recognition tasks.

Contrastive Learning Face Recognition +1

Pixel-Level Face Image Quality Assessment for Explainable Face Recognition

1 code implementation21 Oct 2021 Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Kiran Raja, Arjan Kuijper

To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model.

Face Image Quality Face Image Quality Assessment +1

The Effect of Wearing a Face Mask on Face Image Quality

no code implementations21 Oct 2021 Biying Fu, Florian Kirchbuchner, Naser Damer

This work studies, for the first time, the effect of wearing a face mask on face image quality by utilising state-of-the-art face image quality assessment methods of different natures.

Face Image Quality Face Image Quality Assessment +2

ElasticFace: Elastic Margin Loss for Deep Face Recognition

3 code implementations20 Sep 2021 Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

The recent state-of-the-art face recognition solutions proposed to incorporate a fixed penalty margin on commonly used classification loss function, softmax loss, in the normalized hypersphere to increase the discriminative power of face recognition models, by minimizing the intra-class variation and maximizing the inter-class variation.

 Ranked #1 on Face Recognition on IJB-B (TAR @ FAR=0.0001 metric)

Face Recognition Face Verification

Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection

2 code implementations16 Sep 2021 Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

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 securing face recognition systems.

Domain Adaptation Face Presentation Attack Detection +1

PW-MAD: Pixel-wise Supervision for Generalized Face Morphing Attack Detection

no code implementations23 Aug 2021 Naser Damer, Noemie Spiller, Meiling Fang, Fadi Boutros, Florian Kirchbuchner, Arjan Kuijper

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.

Face Morphing Attack Detection

ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation

no code implementations20 Aug 2021 Naser Damer, Kiran Raja, Marius Süßmilch, Sushma Venkatesh, Fadi Boutros, Meiling Fang, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper

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 border checks.

Face Recognition Generative Adversarial Network

My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition

no code implementations2 Aug 2021 Pedro C. Neto, Fadi Boutros, João Ribeiro Pinto, Mohsen Saffari, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso

The recent Covid-19 pandemic and the fact that wearing masks in public is now mandatory in several countries, created challenges in the use of face recognition systems (FRS).

Face Recognition Triplet

MixFaceNets: Extremely Efficient Face Recognition Networks

1 code implementation27 Jul 2021 Fadi Boutros, Naser Damer, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper

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 Kernels.

Face Verification Lightweight Face Recognition

Demographic Fairness in Biometric Systems: What do the Experts say?

no code implementations31 May 2021 Christian Rathgeb, Pawel Drozdowski, Naser Damer, Dinusha C. Frings, Christoph Busch

Algorithmic decision systems have frequently been labelled as "biased", "racist", "sexist", or "unfair" by numerous media outlets, organisations, and researchers.

Fairness Management

Masked Face Recognition: Human vs. Machine

no code implementations2 Mar 2021 Naser Damer, Fadi Boutros, Marius Süßmilch, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper

This work provides a joint evaluation and in-depth analyses of the face verification performance of human experts in comparison to state-of-the-art automatic FR solutions.

Face Recognition Face Verification

A Comprehensive Study on Face Recognition Biases Beyond Demographics

no code implementations2 Mar 2021 Philipp Terhörst, Jan Niklas Kolf, Marco Huber, Florian Kirchbuchner, Naser Damer, Aythami Morales, Julian Fierrez, Arjan Kuijper

However, to enable a trustworthy FR technology, it is essential to know the influence of an extended range of facial attributes on FR beyond demographics.

Attribute Decision Making +1

Self-restrained Triplet Loss for Accurate Masked Face Recognition

1 code implementation2 Mar 2021 Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

Using the face as a biometric identity trait is motivated by the contactless nature of the capture process and the high accuracy of the recognition algorithms.

Face Recognition Triplet

MAAD-Face: A Massively Annotated Attribute Dataset for Face Images

1 code implementation2 Dec 2020 Philipp Terhörst, Daniel Fährmann, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

In this work, we propose MAADFace, a new face annotations database that is characterized by the large number of its high-quality attribute annotations.

Attribute Face Recognition

Micro Stripes Analyses for Iris Presentation Attack Detection

no code implementations28 Oct 2020 Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

In this paper, we propose a lightweight framework to detect iris presentation attacks by extracting multiple micro-stripes of expanded normalized iris textures.

Iris Recognition Iris Segmentation

On Benchmarking Iris Recognition within a Head-mounted Display for AR/VR Application

no code implementations20 Oct 2020 Fadi Boutros, Naser Damer, Kiran Raja, Raghavendra Ramachandra, Florian Kirchbuchner, Arjan Kuijper

Motivated by the performance of iris recognition, we also propose the continuous authentication of users in a non-collaborative capture setting in HMD.

Benchmarking Iris Recognition

Beyond Identity: What Information Is Stored in Biometric Face Templates?

no code implementations21 Sep 2020 Philipp Terhörst, Daniel Fährmann, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

For evaluating the predictability of the attributes, we trained a massive attribute classifier that is additionally able to accurately state its prediction confidence.

Attribute Face Recognition +1

MIPGAN -- Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN

no code implementations3 Sep 2020 Haoyu Zhang, Sushma Venkatesh, Raghavendra Ramachandra, Kiran Raja, Naser Damer, Christoph Busch

Extensive experiments are carried out to assess the FRS's vulnerability against the proposed morphed face generation technique on three types of data such as digital images, re-digitized (printed and scanned) images, and compressed images after re-digitization from newly generated MIPGAN Face Morph Dataset.

Face Generation Face Recognition +2

Unsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition

1 code implementation21 Feb 2020 Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

Current research on soft-biometrics showed that privacy-sensitive information can be deduced from biometric templates of an individual.

Face Recognition

Post-Comparison Mitigation of Demographic Bias in Face Recognition Using Fair Score Normalization

1 code implementation10 Feb 2020 Philipp Terhörst, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

In contrast to previous works, our fair normalization approach enhances the overall performance by up to 53. 2% at false match rate of 0. 001 and up to 82. 9% at a false match rate of 0. 00001.

Face Recognition Fairness

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