Recognizing Thousands of Legal Entities through Instance-based Visual Classification

Valentin Leveau 1, 2 Alexis Joly 1 Olivier Buisson 2 Pierre Letessier 2 Patrick Valduriez 1
1 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This paper considers the problem of recognizing legal en-tities in visual contents in a similar way to named-entity recognizers for text documents. Whereas previous works were restricted to the recognition of a few tens of logotypes, we generalize the problem to the recognition of thousands of legal persons, each being modeled by a rich corporate identity automatically built from web images. We intro-duce a new geometrically-consistent instance-based classifi-cation method that is shown to outperform state-of-the-art techniques on several challenging datasets while being much more scalable. Further experiments performed on an au-tomatic web crawl of 5,824 legal entities demonstrates the scalability of the approach.
Type de document :
Communication dans un congrès
ACM Multimedia, Nov 2014, Orlando, FL, United States. The 22nd ACM International Conference on Multimedia - November 3-7, 2014 | Orlando, FL, USA, 2014, 〈http://acmmm.org/2014/〉. 〈10.1145/2647868.2655038〉
Liste complète des métadonnées

Littérature citée [19 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01077508
Contributeur : Valentin Leveau <>
Soumis le : samedi 25 octobre 2014 - 00:06:52
Dernière modification le : vendredi 20 juillet 2018 - 22:44:01
Document(s) archivé(s) le : lundi 26 janvier 2015 - 10:06:20

Fichier

instance_based_classification_...
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Valentin Leveau, Alexis Joly, Olivier Buisson, Pierre Letessier, Patrick Valduriez. Recognizing Thousands of Legal Entities through Instance-based Visual Classification. ACM Multimedia, Nov 2014, Orlando, FL, United States. The 22nd ACM International Conference on Multimedia - November 3-7, 2014 | Orlando, FL, USA, 2014, 〈http://acmmm.org/2014/〉. 〈10.1145/2647868.2655038〉. 〈hal-01077508〉

Partager

Métriques

Consultations de la notice

481

Téléchargements de fichiers

310