5 citations · 5 across the 2 of their papers we have counts for
8 papers
Training face verification models from generated face identity data
Dennis Conway, Loic Simon, Alexis Lechervy +1
Machine learning tools are becoming increasingly powerful and widely used. Unfortunately membership attacks, which seek to uncover information from data sets used in machine learni…
Towards a General Model of Knowledge for Facial Analysis by Multi-Source Transfer Learning
Valentin Vielzeuf, Alexis Lechervy, Stéphane Pateux +1
This paper proposes a step toward obtaining general models of knowledge for facial analysis, by addressing the question of multi-source transfer learning. More precisely, the propo…
Multi-Level Sensor Fusion with Deep Learning
Valentin Vielzeuf, Alexis Lechervy, Stéphane Pateux +1
In the context of deep learning, this article presents an original deep network, namely CentralNet, for the fusion of information coming from different sensors. This approach is de…
RPNet: an End-to-End Network for Relative Camera Pose Estimation
Sovann En, Alexis Lechervy, Frédéric Jurie
This paper addresses the task of relative camera pose estimation from raw image pixels, by means of deep neural networks. The proposed RPNet network takes pairs of images as input…
CentralNet: a Multilayer Approach for Multimodal Fusion
Valentin Vielzeuf, Alexis Lechervy, Stéphane Pateux +1
This paper proposes a novel multimodal fusion approach, aiming to produce best possible decisions by integrating information coming from multiple media. While most of the past mult…
An Occam's Razor View on Learning Audiovisual Emotion Recognition with Small Training Sets
Valentin Vielzeuf, Corentin Kervadec, Stéphane Pateux +2
This paper presents a light-weight and accurate deep neural model for audiovisual emotion recognition. To design this model, the authors followed a philosophy of simplicity, drasti…