Deep multi-instance learning for end-to-end person re-identification
Deep multi-instance learning for end-to-end person re-identification
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Scope and Contents
Contents
In this paper, we introduce a deep multi-instance learning framework to boost the instance-level person re-identification performance. Motivated by the observation of considerably dramatic and complex varieties of visual appearances in many current person re-identification datasets, we explicitly represent a deep feature representation learning met...
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Full title
Deep multi-instance learning for end-to-end person re-identification
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TN_cdi_proquest_journals_2044094136
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2044094136
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ISSN
1380-7501
E-ISSN
1573-7721
DOI
10.1007/s11042-017-4896-2
