336 citations · 1.4k across the 70 of their papers we have counts for
9 papers · 1 filter
A cascaded multiple-speaker localization and tracking system
Xiaofei Li, Yutong Ban, Laurent Girin +2
This paper presents an online multiple-speaker localization and tracking method, as the INRIA-Perception contribution to the LOCATA Challenge 2018. First, the recursive least-squar…
Tracking Multiple Audio Sources with the von Mises Distribution and Variational EM
Yutong Ban, Xavier Alameda-PIneda, Christine Evers +1
In this paper we address the problem of simultaneously tracking several moving audio sources, namely the problem of estimating source trajectories from a sequence of observed featu…
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers
Yutong Ban, Xavier Alameda-Pineda, Laurent Girin +1
In this paper we address the problem of tracking multiple speakers via the fusion of visual and auditory information. We propose to exploit the complementary nature of these two mo…
Online Localization and Tracking of Multiple Moving Speakers in Reverberant Environments
Xiaofei Li, Yutong Ban, Laurent Girin +2
We address the problem of online localization and tracking of multiple moving speakers in reverberant environments. The paper has the following contributions. We use the direct-pat…
DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model
Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda +1
In this paper, we address the problem of how to robustly train a ConvNet for regression, or deep robust regression. Traditionally, deep regression employs the L2 loss function, kno…
Every Smile is Unique: Landmark-Guided Diverse Smile Generation
Wei Wang, Xavier Alameda-Pineda, Dan Xu +3
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…
Cross-Paced Representation Learning with Partial Curricula for Sketch-based Image Retrieval
Dan Xu, Xavier Alameda-Pineda, Jingkuan Song +2
In this paper we address the problem of learning robust cross-domain representations for sketch-based image retrieval (SBIR). While most SBIR approaches focus on extracting low- an…
A Comprehensive Analysis of Deep Regression
Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda +1
Deep learning revolutionized data science, and recently its popularity has grown exponentially, as did the amount of papers employing deep networks. Vision tasks, such as human pos…
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
Dan Xu, Wanli Ouyang, Xavier Alameda-Pineda +3
Recent works have shown that exploiting multi-scale representations deeply learned via convolutional neural networks (CNN) is of tremendous importance for accurate contour detectio…