Weakly Supervised Object Localization with Large Fisher Vectors

Josip Krapac; Siniša Šegvić

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Paper

Weakly Supervised Object Localization with Large Fisher Vectors

Topics: Features Extraction; Object Detection and Localization

In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, 44-53, 2015 , Berlin, Germany

Authors: Josip Krapac and Siniša Šegvić

Affiliation: Faculty of Electrical Engineering and Computing and University of Zagreb, Croatia

Keyword(s): Weakly Supervised Object Localization, Fisher Vectors, Sparse Classification Models.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: We propose a novel method for learning object localization models in a weakly supervised manner, by employing images annotated with object class labels but not with object locations. Given an image, the learned model predicts both the presence of the object class in the image and the bounding box that determines the object location. The main ingredients of our method are a large Fisher vector representation and a sparse classification model enabling efficient evaluation of patch scores. The method is able to reliably detect very small objects with some intra-class variation in reasonable time. Experimental validation has been performed on a public dataset and we report localization performance comparable to strongly supervised approaches.

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Paper citation in several formats:

Krapac, J. and Šegvić, S. (2015). Weakly Supervised Object Localization with Large Fisher Vectors. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 44-53. DOI: 10.5220/0005294900440053

@conference{visapp15,
author={Josip Krapac. and Siniša Šegvić.},
title={Weakly Supervised Object Localization with Large Fisher Vectors},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={44-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005294900440053},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Weakly Supervised Object Localization with Large Fisher Vectors
SN - 978-989-758-090-1
IS - 2184-4321
AU - Krapac, J.
AU - Šegvić, S.
PY - 2015
SP - 44
EP - 53
DO - 10.5220/0005294900440053
PB - SciTePress