Learning comprehensive global features in person re-identification: Ensuring discriminativeness of more local regions
•A novel baseline for person re-identification is proposed to learn comprehensive global embedding, ensuring that more local regions (the number of local regions is manually defined) of global feature maps are discriminative.•A Non-parameterized Local Classifier (NLC) module is designed to obtain a...
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Published in | Pattern recognition Vol. 134; p. 109068 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.02.2023
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Subjects | |
Online Access | Get full text |
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