Publications associées à Sous-titrage pour sourds et malentendants

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

This text, accompanied by a ‘gospel’ that I made by montaging the US-recorded captions, is an attempt for re-narrating Marshall Plan’s discourse on the working class, aka the so-called ‘free labor’ of the US against the ‘communist labor’ of the “Soviet thr ...

EPFL Press2023

Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images

Devis Tuia, Christel Marie Tartini-Chappuis, Li Mi, Siran Li

Image-based retrieval in large Earth observation archives is difficult, because one needs to navigate across thousands of candidate matches only with the proposition image as a guide. By using text as a query language, the retrieval system gains in usabili ...

2022

Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

Karl Aberer, Rémi Philippe Lebret, Alireza Mohammadshahi

In this paper, we propose a new approach to learn multimodal multilingual embeddings for matching images and their relevant captions in two languages. We combine two existing objective functions to make images and captions close in a joint embedding space ...

Association for Computational Linguistics2019

A Constrained Latent Variable Model

Pascal Fua, Mathieu Salzmann, Raquel Urtasun, Aydin Varol

Latent variable models provide valuable compact representations for learning and inference in many computer vision tasks. However, most existing models cannot directly encode prior knowledge about the specific problem at hand. In this paper, we introduce a ...

Ieee2012

A Large-Scale Database of Images and Captions for Automatic Face Naming

Barbara Caputo, Jie Luo, Vittorio Ferrari

We present a large scale database of images and captions, designed for supporting research on how to use captioned images from the Web for training visual classifiers. It consists of more than 125,000 images of celebrities from different fields downloaded ...

2011

A Large-Scale Database of Images and Captions for Automatic Face Naming

Barbara Caputo, Jie Luo, Vittorio Ferrari

Idiap2011

Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Barbara Caputo, Jie Luo, Vittorio Ferrari

Given a corpus of news items consisting of images accompanied by text captions, we want to find out “who’s doing what”, i.e. associate names and action verbs in the captions to the face and body pose of the persons in the images. We present a joint model f ...

MIT Press2009

Multimedia Terminal Architecture: An Inter-Operable Approach

Marco Mattavelli, Beilu Shao

This paper addresses the inter-operability problem of multimedia terminal in media content delivery over heterogeneous networks and devices. We design and implement a terminal which includes a content browser providing presentation, navigation and interact ...

IEEE Computer Society Press2008

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Sous-titrage pour sourds et malentendants

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images

Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

A Constrained Latent Variable Model

A Large-Scale Database of Images and Captions for Automatic Face Naming

A Large-Scale Database of Images and Captions for Automatic Face Naming

Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Multimedia Terminal Architecture: An Inter-Operable Approach

A MPEG-4 virtual human animation engine for interactive web based applications

Video OCR for Sport Video Annotation and Retrieval

Graph Chatbot

Chattez avec Graph Search

Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images

A MPEG-4 virtual human animation engine for interactive web based applications

A Constrained Latent Variable Model

A Large-Scale Database of Images and Captions for Automatic Face Naming

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

Multimedia Terminal Architecture: An Inter-Operable Approach

Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

A Large-Scale Database of Images and Captions for Automatic Face Naming

Video OCR for Sport Video Annotation and Retrieval