348 citations
- Technicolor (Germany)DE14 papers
- Technicolor (United States)US11 papers
- Centre National de la Recherche ScientifiqueFR9 papers
- Centre Inria de l'Université de RennesFR6 papers
- Institut national de recherche en sciences et technologies du numériqueFR4 papers
- Valeo (France)FR4 papers
- École Polytechnique Fédérale de LausanneCH3 papers
- Institut de Recherche en Informatique et Systèmes AléatoiresFR3 papers
- Intel (United Kingdom)GB3 papers
- Max Planck Institute for InformaticsDE3 papers
- Rutgers, The State University of New JerseyUS3 papers
- Université de RennesFR3 papers
7 papers · 1 filter
Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models
Alberto Lumbreras, Julien Velcin, Marie Guégan +1
We present a dual-view mixture model to cluster users based on their features and latent behavioral functions. Every component of the mixture model represents a probability density…
MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets
Corentin Hardy, Erwan Le Merrer, Bruno Sericola
A recent technical breakthrough in the domain of machine learning is the discovery and the multiple applications of Generative Adversarial Networks (GANs). Those generative models…
MediaEval 2018: Predicting Media Memorability Task
Romain Cohendet, Claire-Hélène Demarty, Ngoc Duong +4
In this paper, we present the Predicting Media Memorability task, which is proposed as part of the MediaEval 2018 Benchmarking Initiative for Multimedia Evaluation. Participants ar…
A Flexible Convolutional Solver with Application to Photorealistic Style Transfer
Gilles Puy, Patrick Pérez
We propose a new flexible deep convolutional neural network (convnet) to perform fast visual style transfer. In contrast to existing convnets that address the same task, our archit…
Learning how to be robust: Deep polynomial regression
Juan-Manuel Perez-Rua, Tomas Crivelli, Patrick Bouthemy +1
Polynomial regression is a recurrent problem with a large number of applications. In computer vision it often appears in motion analysis. Whatever the application, standard methods…
Weakly Supervised Representation Learning for Unsynchronized Audio-Visual Events
Sanjeel Parekh, Slim Essid, Alexey Ozerov +3
Audio-visual representation learning is an important task from the perspective of designing machines with the ability to understand complex events. To this end, we propose a novel…