Heterogeneous Face Recognition with CNNs

Shreyas Saxena 1 Jakob Verbeek 1
1 Thoth - Apprentissage de modèles à partir de données massives
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann
Abstract : Heterogeneous face recognition aims to recognize faces across different sensor modalities. Typically, gallery images are normal visible spectrum images, and probe images are infrared images or sketches. Recently significant improvements in visible spectrum face recognition have been obtained by CNNs learned from very large training datasets. In this paper, we are interested in the question to what extent the features from a CNN pre-trained on visible spectrum face images can be used to perform heterogeneous face recognition. We explore different metric learning strategies to reduce the discrepancies between the different modalities. Experimental results show that we can use CNNs trained on visible spectrum images to obtain results that are on par or improve over the state-of-the-art for heterogeneous recognition with near-infrared images and sketches.
Type de document :
Communication dans un congrès
Gang Hua; Hervé Jégou. ECCV TASK-CV 2016 Workshops, Oct 2016, Amsterdam, Netherlands. Springer, European Conference on Computer Vision Workshops, 9915 (Part III), pp.483-491, Lecture Notes in Computer Science. 〈10.​1007/​978-3-319-49409-8_​40〉
Liste complète des métadonnées

Littérature citée [25 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01367455
Contributeur : Thoth Team <>
Soumis le : vendredi 16 septembre 2016 - 10:57:08
Dernière modification le : lundi 25 septembre 2017 - 10:08:02
Document(s) archivé(s) le : samedi 17 décembre 2016 - 13:00:53

Fichier

0014.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Shreyas Saxena, Jakob Verbeek. Heterogeneous Face Recognition with CNNs. Gang Hua; Hervé Jégou. ECCV TASK-CV 2016 Workshops, Oct 2016, Amsterdam, Netherlands. Springer, European Conference on Computer Vision Workshops, 9915 (Part III), pp.483-491, Lecture Notes in Computer Science. 〈10.​1007/​978-3-319-49409-8_​40〉. 〈hal-01367455〉

Partager

Métriques

Consultations de
la notice

723

Téléchargements du document

943