Virtual and Real World Adaptation for Pedestrian Detection
Pedestrian detection is of paramount interest for many applications. Most promising detectors rely on discriminatively learnt classifiers, i.e., trained with annotated samples. However, the annotation step is a human intensive and subjective task worth to be minimized. By using virtual worlds we can...
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Détails bibliographiques
Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 36(2014), 4 vom: 01. Apr., Seite 797-809
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Auteur principal: |
Vázquez, David
(Auteur) |
Autres auteurs: |
López, Antonio M,
Marín, Javier,
Ponsa, Daniel,
Gerónimo, David |
Format: | Article en ligne
|
Langue: | English |
Publié: |
2014
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Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
|
Sujets: | Journal Article
Research Support, Non-U.S. Gov't |