activity
20182022
most citedActive Speaker Detection as a Multi-Objective Optimization with Uncertainty-based Multimodal Fusion

9 citations · 14 across the 5 of their papers we have counts for

collaborators

7 papers

stat.ML20222 cited

Generalised Mutual Information for Discriminative Clustering

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron +4

In the last decade, recent successes in deep clustering majorly involved the mutual information (MI) as an unsupervised objective for training neural networks with increasing regul…

cs.CV2022

A Multi-stage deep architecture for summary generation of soccer videos

Melissa Sanabria, Frédéric Precioso, Pierre-Alexandre Mattei +1

Video content is present in an ever-increasing number of fields, both scientific and commercial. Sports, particularly soccer, is one of the industries that has invested the most in…

cs.SD20219 cited

Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-based Multimodal Fusion

Baptiste Pouthier, Laurent Pilati, Leela K. Gudupudi +2

It is now well established from a variety of studies that there is a significant benefit from combining video and audio data in detecting active speakers. However, either of the mo…

stat.ML2020

From text saliency to linguistic objects: learning linguistic interpretable markers with a multi-channels convolutional architecture

Laurent Vanni, Marco Corneli, Damon Mayaffre +1

A lot of effort is currently made to provide methods to analyze and understand deep neural network impressive performances for tasks such as image or text classification. These met…

cs.CV2019

Revisiting Deep Architectures for Head Motion Prediction in 360° Videos

Miguel Fabian Romero Rondon, Lucile Sassatelli, Ramon Aparicio Pardo +1

We consider predicting the user's head motion in 360-degree videos, with 2 modalities only: the past user's positions and the video content (not knowing other users' traces). We ma…

cs.LG20193 cited

Adaptive Bayesian Linear Regression for Automated Machine Learning

Weilin Zhou, Frederic Precioso

To solve a machine learning problem, one typically needs to perform data preprocessing, modeling, and hyperparameter tuning, which is known as model selection and hyperparameter op…