Unsupervised domain adaptive re-identification: Theory and practice

Pattern Recognition, pp. 1071732020.

Cited by: 53|Bibtex|Views44|DOI:https://doi.org/10.1016/j.patcog.2019.107173
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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

Abstract We study the problem of unsupervised domain adaptive re-identification (re-ID) which is an active topic in computer vision but lacks a theoretical foundation. We first extend existing unsupervised domain adaptive classification theories to re-ID tasks. Concretely, we introduce some assumptions on the extracted feature space and...More

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