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Matching Seqlets: An Unsupervised Approach for Locality Preserving Sequence Matching

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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, Hazim Kemal Ekenel, Mohammad Saeed Rad

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, Seyedbehzad Bozorgtabar, Hazim Kemal Ekenel, Mohammad Saeed Rad

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

Adaptive Social Learning for Tracking Rare Transition Markov Chains

Ali H. Sayed, Virginia Bordignon, Malek Khammassi

Adaptive Social Learning (ASL) enables consistent truth learning in nonstationary environments. In this framework, agents linked by a graph, exchange their local beliefs with neighbors to track some underlying state of interest. This state can drift over t ...

European Signal Processing Conference, EUSIPCO2024

Beyond Essentials: Nuanced and Diverse Text-to-video Retrieval

Yuchen Yang

The field of text-to-video retrieval has advanced significantly with the evolution of language models and large-scale pre-training on generated caption-video pairs. Current methods predominantly focus on visual and event-based details, making retrieval lar ...

Institute of Electrical and Electronics Engineers Inc.2024

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

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

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

Distributed Adaptive Learning Under Communication Constraints

Ali H. Sayed

We consider a network of agents that must solve an online optimization problem from continual observation of streaming data. To this end, the agents implement a distributed cooperative strategy where each agent is allowed to perform local exchange of infor ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Face Frontalization for Cross-Pose Facial Expression Recognition

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

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

Data-driven models in fusion exhaust: AI methods and perspectives

Yoeri Renier Johannes Poels

A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved mod ...

IOP Publishing Ltd2024

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

Hyperdimensional computing with holographic and adaptive encoder

Alejandro Hernández Cano

Introduction: Brain-inspired computing has become an emerging field, where a growing number of works focus on developing algorithms that bring machine learning closer to human brains at the functional level. As one of the promising directions, Hyperdimensi ...

2024

Every Smile is Unique: Landmark-Guided Diverse Smile Generation

Pascal Fua, Wei Wang

Each smile is unique: one person surely smiles in different ways (e.g. closing/opening the eyes or mouth). Given one input image of a neutral face, can we generate multiple smile videos with distinctive characteristics? To tackle this one-to-many video gen ...

IEEE2018

EdgeFace: Efficient Face Recognition Model for Edge Devices

Hatef Otroshi Shahreza

In this paper, we present EdgeFace - a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt. By effectively combining the strengths of both CNN and Transformer models, and a low rank linear layer, EdgeFace achi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving

Jean-Philippe Thiran, Anil Yuce, Hua Gao, Gabriel Louis Cuendet

Driving requires the constant coordination of many body systems and full attention of the person. Cognitive distraction (subsidiary mental load) of the driver is an important factor that decreases attention and responsiveness, which may result in human err ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Learning to Boost the Performance of Stable Nonlinear Systems

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

The growing scale and complexity of safety-critical control systems underscore the need to evolve current control architectures aiming for the unparalleled performances achievable through state-of-the-art optimization and machine learning algorithms. Howev ...

2024

Physics-based Reconstruction and Animation of Humans

Alexandru Eugen Ichim

Creating digital representations of humans is of utmost importance for applications ranging from entertainment (video games, movies) to human-computer interaction and even psychiatrical treatments. What makes building credible digital doubles difficult is ...

EPFL2017

A journey toward generalizable trajectory forecasting models

Mohammadhossein Bahari

Autonomous driving is a revolutionary technology that has seen considerable advancements through the adoption of deep learning solutions. One of the major challenges in this field is the interaction with other road users. This interaction necessitates a "t ...

EPFL2024

Evaluating the Sensitivity to Virtual Characters Facial Asymmetry in Emotion Synthesis

Ronan Boulic, Junghyun Ahn, Nan Wang

The use of expressive Virtual Characters is an effective complementary means of communication for social networks offering multi-user 3D-chatting environment. In such context the facial expression channel offers a rich medium to translate the on-going emot ...

Taylor & Francis2017