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Vulnerability of Face Recognition to Deep Morphing

Publications associées (52)

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Contextually Plausible and Diverse 3D Human Motion Prediction

Mathieu Salzmann, Fatemehsadat Saleh

We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses. In this context, a popular approach consists of using a Conditional Variational Autoencoder (CVAE). How ...

IEEE2021

Learning How to Smile: Expression Video Generation With Conditional Adversarial Recurrent Nets

Wei Wang

While several research studies have focused on analyzing human behavior and, in particular, emotional signals from visual data, the problem of synthesizing face video sequences with specific attributes (e.g. age, facial expressions) received much less atte ...

2020

Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks

Sébastien Marcel, Eklavya Sarkar, Laurent Colbois

Morphing attacks is a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control. ...

Idiap2020

Deepfake detection: humans vs. machines

Sébastien Marcel

Deepfake videos, where a person’s face is automatically swapped with a face of someone else, are becoming easier to generate with more realistic results. In response to the threat such manipulations can pose to our trust in video evidence, several large da ...

Idiap2020

We propose FedGP, a framework for privacy-preserving data release in the federated learning setting. We use generative adversarial networks, generator components of which are trained by FedAvg algorithm, to draw private artificial data samples and empirica ...

IEEE COMPUTER SOC2020

Editing in Style: Uncovering the Local Semantics of GANs

Sabine Süsstrunk, Edo Collins

While the quality of GAN image synthesis has improved tremendously in recent years, our ability to control and condition the output is still limited. Focusing on StyleGAN, we introduce a simple and effective method for making local, semantically-aware edit ...

2020

It is becoming increasingly easy to automatically replace a face of one person in a video with the face of another person by using a pre-trained generative adversarial network (GAN). Recent public scandals, e.g., the faces of celebrities being swapped onto ...

2019

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Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation between any two image domains using a single attribute or require training data ...

2019

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ACADEMIC PRESS INC ELSEVIER SCIENCE2019

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Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expression recognition accuracy despite having small number of real training images. ...

IEEE2019