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Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association
[article]
2018
arXiv
pre-print
Person re-identification is an important task that requires learning discriminative visual features for distinguishing different person identities. Diverse auxiliary information has been utilized to improve the visual feature learning. In this paper, we propose to exploit natural language description as additional training supervisions for effective visual features. Compared with other auxiliary information, language can describe a specific person from more compact and semantic visual aspects,
arXiv:1808.01571v1
fatcat:rhtkqcjxubcezm7gqwru5ewklu