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2020 | OriginalPaper | Buchkapitel

Details for Person Re-identification Baseline

verfasst von : Zhong Zhang, Haijia Zhang, Shuang Liu

Erschienen in: Artificial Intelligence in China

Verlag: Springer Singapore

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Abstract

In this paper, we evaluate the performance of person re-identification (Re-ID) baseline under different implementation details including resize ratio of the pedestrian image, batch size and basic learning rate. To this end, we employ ResNet-50 as the classification model by modifying the original FC layer and apply a classifier to compute identity prediction values. We perform amounts of experiments to assess the effects of these implementation details on Market-1501 and experimental results show that these implementation details are very important for person Re-ID.

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Metadaten
Titel
Details for Person Re-identification Baseline
verfasst von
Zhong Zhang
Haijia Zhang
Shuang Liu
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-0187-6_54

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