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Authors: Alexander Gillert 1 and Uwe Freiherr von Lukas 2 ; 1

Affiliations: 1 Fraunhofer Institute for Computer Graphics Research IGD, Rostock, Germany ; 2 Department of Computer Science, University of Rostock, Germany

Keyword(s): Fine-grained Classification, Out-of-Distribution Detection, Open Set Recognition.

Abstract: We analyze the two very similar problems of Out-of-Distribution (OOD) Detection and Open Set Recognition (OSR) in the context of fine-grained classification. Both problems are about detecting object classes that a classifier was not trained on, but while the former aims to reject invalid inputs, the latter aims to detect valid but unknown classes. Previous works on OOD detection and OSR methods are evaluated mostly on very simple datasets or datasets with large inter-class variance and perform poorly in the fine-grained setting. In our experiments, we show that object detection works well to recognize invalid inputs and techniques from the field of fine-grained classification, like individual part detection or zooming into discriminative local regions, are helpful for fine-grained OSR.

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Paper citation in several formats:
Gillert, A. and von Lukas, U. (2021). Towards Combined Open Set Recognition and Out-of-Distribution Detection for Fine-grained Classification. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 225-233. DOI: 10.5220/0010340702250233

@conference{visapp21,
author={Alexander Gillert. and Uwe Freiherr {von Lukas}.},
title={Towards Combined Open Set Recognition and Out-of-Distribution Detection for Fine-grained Classification},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={225-233},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010340702250233},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Towards Combined Open Set Recognition and Out-of-Distribution Detection for Fine-grained Classification
SN - 978-989-758-488-6
IS - 2184-4321
AU - Gillert, A.
AU - von Lukas, U.
PY - 2021
SP - 225
EP - 233
DO - 10.5220/0010340702250233
PB - SciTePress

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