Arcface: Additive angular margin loss for deep face recognition
One of the main challenges in feature learning using Deep Convolutional Neural Networks
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …
Unsupervised cross-domain image generation
We study the problem of transferring a sample in one domain to an analog sample in
another domain. Given two related domains, S and T, we would like to learn a generative …
another domain. Given two related domains, S and T, we would like to learn a generative …
Mofa: Model-based deep convolutional face autoencoder for unsupervised monocular reconstruction
A Tewari, M Zollhofer, H Kim… - Proceedings of the …, 2017 - openaccess.thecvf.com
In this work we propose a novel model-based deep convolutional autoencoder that
addresses the highly challenging problem of reconstructing a 3D human face from a single …
addresses the highly challenging problem of reconstructing a 3D human face from a single …
On the reconstruction of face images from deep face templates
State-of-the-art face recognition systems are based on deep (convolutional) neural
networks. Therefore, it is imperative to determine to what extent face templates derived from …
networks. Therefore, it is imperative to determine to what extent face templates derived from …
Synthesizing normalized faces from facial identity features
We present a method for synthesizing a frontal, neutral-expression image of a person's face,
given an input face photograph. This is achieved by learning to generate facial landmarks …
given an input face photograph. This is achieved by learning to generate facial landmarks …
Template inversion attack against face recognition systems using 3d face reconstruction
HO Shahreza, S Marcel - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Face recognition systems are increasingly being used in different applications. In such
systems, some features (also known as embeddings or templates) are extracted from each …
systems, some features (also known as embeddings or templates) are extracted from each …
Reversing the irreversible: A survey on inverse biometrics
M Gomez-Barrero, J Galbally - Computers & Security, 2020 - Elsevier
With the widespread use of biometric recognition, several issues related to the privacy and
security provided by this technology have been recently raised and analysed. As a result …
security provided by this technology have been recently raised and analysed. As a result …
Recent progress of face image synthesis
Face synthesis has been a fascinating yet challenging problem in computer vision and
machine learning. Its main research effort is to design algorithms to generate photo-realistic …
machine learning. Its main research effort is to design algorithms to generate photo-realistic …
Reconstruct face from features based on genetic algorithm using GAN generator as a distribution constraint
Face recognition based on deep convolutional neural networks (CNN) shows superior
accuracy performance attributed to the high discriminative features extracted. Yet, the …
accuracy performance attributed to the high discriminative features extracted. Yet, the …
Comprehensive vulnerability evaluation of face recognition systems to template inversion attacks via 3d face reconstruction
HO Shahreza, S Marcel - IEEE Transactions on Pattern …, 2023 - ieeexplore.ieee.org
In this article, we comprehensively evaluate the vulnerability of state-of-the-art face
recognition systems to template inversion attacks using 3D face reconstruction. We propose …
recognition systems to template inversion attacks using 3D face reconstruction. We propose …