Search Results for author:
Found 31 papers, 14 papers with code
Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-adaption and Few-Shot Learning
In previous works, a mobile application was developed using an unmodified commercial off-the-shelf smartphone to recognize whole-body exercises.
Stating Comparison Score Uncertainty and Verification Decision Confidence Towards Transparent Face Recognition
The confidence of a decision is often based on the overall performance of the model or on the image quality.
On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations
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.
Mask-invariant Face Recognition through Template-level Knowledge Distillation
The emergence of the global COVID-19 pandemic poses new challenges for biometrics.
QMagFace: Simple and Accurate Quality-Aware Face Recognition
These variabilities can be measured in terms of face image quality which is defined over the utility of a sample for recognition.
Ranked #1 on
Face Verification
on IJB-B
The Effect of Wearing a Face Mask on Face Image Quality
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.
Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
To achieve this, a model-specific quality value of the input image is estimated and used to build a sample-specific quality regression model.
ElasticFace: Elastic Margin Loss for Deep Face Recognition
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)
Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection
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.
PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation
However, this limits the deployment of such models that contain an extremely large number of parameters to embedded and low-end devices.
Ranked #2 on
Lightweight Face Recognition
on CALFW
PW-MAD: Pixel-wise Supervision for Generalized Face Morphing Attack Detection
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.
ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation
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.
MixFaceNets: Extremely Efficient Face Recognition Networks
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.
Ranked #3 on
Lightweight Face Recognition
on IJB-C
MFR 2021: Masked Face Recognition Competition
These teams successfully submitted 18 valid solutions.
Iris Presentation Attack Detection by Attention-based and Deep Pixel-wise Binary Supervision Network
Iris presentation attack detection (PAD) plays a vital role in iris recognition systems.
MiDeCon: Unsupervised and Accurate Fingerprint and Minutia Quality Assessment based on Minutia Detection Confidence
The implementation is publicly available.
A Comprehensive Study on Face Recognition Biases Beyond Demographics
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.
Masked Face Recognition: Human vs. Machine
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.
Self-restrained Triplet Loss for Accurate Masked Face Recognition
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.
Real Masks and Spoof Faces: On the Masked Face Presentation Attack Detection
Face masks have become one of the main methods for reducing the transmission of COVID-19.
MAAD-Face: A Massively Annotated Attribute Dataset for Face Images
In this work, we propose MAADFace, a new face annotations database that is characterized by the large number of its high-quality attribute annotations.
Micro Stripes Analyses for Iris Presentation Attack Detection
In this paper, we propose a lightweight framework to detect iris presentation attacks by extracting multiple micro-stripes of expanded normalized iris textures.
On Benchmarking Iris Recognition within a Head-mounted Display for AR/VR Application
Motivated by the performance of iris recognition, we also propose the continuous authentication of users in a non-collaborative capture setting in HMD.
Beyond Identity: What Information Is Stored in Biometric Face Templates?
For evaluating the predictability of the attributes, we trained a massive attribute classifier that is additionally able to accurately state its prediction confidence.
The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study
The recent COVID-19 pandemic have increased the value of hygienic and contactless identity verification.
Face Quality Estimation and Its Correlation to Demographic and Non-Demographic Bias in Face Recognition
Face quality assessment aims at estimating the utility of a face image for the purpose of recognition.
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
Face image quality is an important factor to enable high performance face recognition systems.
Ranked #1 on
Face Quality Assessement
on LFW
Demographic Bias in Presentation Attack Detection of Iris Recognition Systems
With the widespread use of biometric systems, the demographic bias problem raises more attention.
Unsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition
Current research on soft-biometrics showed that privacy-sensitive information can be deduced from biometric templates of an individual.
Post-Comparison Mitigation of Demographic Bias in Face Recognition Using Fair Score Normalization
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.
Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures
Generating visible-like face images from thermal images is essential to perform manual and automatic cross-spectrum face recognition.
