Publications related to Matching Seqlets: An Unsupervised Approach for Locality Preserving Sequence Matching

Real-time actuation of a dielectric elastomer actuator neuroprosthesis for facial paralysis

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Stefania Maria Aliki Konstantinidi, Armando Matthieu Walter, Amine Benouhiba

Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his mimic musculature on one or both sides of his face. This condition compromises the patient's communication and facial expressions, and thus dramatically reduce ...

2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Discriminative Deep Feature Visualization for Explainable Face Recognition

Touradj Ebrahimi, Yuhang Lu, Zewei Xu

Despite the huge success of deep convolutional neural networks in face recognition (FR) tasks, current methods lack explainability for their predictions because of their ``black-box'' nature. In recent years, studies have been carried out to give an interp ...

2023

A Novel Framework for Assessment of Deep Face Recognition Systems in Realistic Conditions

Touradj Ebrahimi, Luca Barras, Yuhang Lu

Deep convolutional neural networks have shown remarkable results on face recognition (FR). Despite their significant progress, the performance of current face recognition techniques is often assessed in benchmarks under not always realistic conditions. The ...

2022

Model-based 3D Face Reconstruction

Christophe René Joseph Ecabert

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

EPFL2021

Towards Recognizing Emotion in the Latent Space

Rayan Elalamy

Emotion recognition is usually achieved by collecting features (physiological signals, events, facial expressions, etc.) to predict an emotional ground truth. This ground truth is arguably unreliable due to its subjective nature. In this paper, we introduc ...

IEEE2021

3D Printed Motor-Sensory Module Prototype for Facial Rehabilitation

Jamie Paik, Amir Firouzeh, Matthew Aaron Robertson

This work demonstrates the first 3D printed wearable motor-sensory module prototype designed for facial rehabilitation, focusing on facial paralysis. The novelty of the work lies in the fast fabrication of the first fully soft working prototype, including ...

MARY ANN LIEBERT, INC2022

Multi-Modal Recurrent Attention Networks for Facial Expression Recognition

Jiyoung Lee, Seungryong Kim

Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Kshitij Sharma, Jennifer Kaitlyn Olsen

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

ASSOC COMPUTING MACHINERY2020

Context-Aware Emotion Recognition Networks

Jiyoung Lee, Seungryong Kim

Traditional techniques for emotion recognition have focused on the facial expression analysis only, thus providing limited ability to encode context that comprehensively represents the emotional responses. We present deep networks for context-aware emotion ...

IEEE2019

Multimodal person recognition in audio-visual streams

Do Hoang Nam Le

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

EPFL2019

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel

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

Learn to synthesize and synthesize to learn

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel, Seyedbehzad Bozorgtabar

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

What Face and Body Shapes Can Tell Us About Height

Pascal Fua, Helge Jochen Rhodin, Semih Günel

Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance. However, it is also very challenging without absolute scale information. Here, we examine the rarely addressed case, where camer ...

IEEE COMPUTER SOC2019

Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network

Sébastien Marcel, André Anjos, Zohreh Mostaani

Face recognition is a mainstream biometric authentication method. However, vulnerability to presentation attacks (a.k.a spoofing) limits its usability in unsupervised applications. Even though there are many methods available for tackling presentation atta ...

2020

Facing Employers and Customers: What Do Gaze and Expressions Tell About Soft Skills?

Jean-Marc Odobez, Daniel Gatica-Perez, Rémy Alain Siegfried, Skanda Muralidhar

Eye gaze and facial expressions are central to face-to-face social interactions. These behavioral cues and their connections to first impressions have been widely studied in psychology and computing literature, but limited to a single situation. Utilizing ...

ASSOC COMPUTING MACHINERY2018

Face Frontalization for Cross-Pose Facial Expression Recognition

Jean-Philippe Thiran, Christophe René Joseph Ecabert, Hazim Kemal Ekenel, Deniz Engin

In this paper, we have explored the effect of pose normalization for cross-pose facial expression recognition. We have first presented an expression preserving face frontalization method. After face frontalization step, for facial expression representation ...

IEEE COMPUTER SOC2018

Variational Methods for Human Modeling

Timur Bagautdinov

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

EPFL2018