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SCI."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Person and vehicle re-identification has been a popular subject in the field of the computer vision technologies. Existing closed-set re-identification surpasses human-level accuracies on commonly used benchmarks, and the research focus for re-identification is shifting to the open world-setting. The latter setting is more suitable for practical applications, however, is less developed due to its challenges. On the other hand, existing research is more focused on person re-identification, even though both, person and vehicle, are important components for smart city applications. This review attempts to combine for the first time the problem of person and vehicle re-identification under closed and open settings, its challenges, and the existing research. Specifically, we start from the origin of the re-identification task and then summarize state-of-the-art research based on deep learning in different scenarios: person or vehicle or unified re-identification in closed- and open-world settings. Additionally, we analyse a new method for solving the re-identification task using the Transformer, a model architecture that relies entirely on an attention mechanism, which shows promising results. This survey facilitates future research by providing a summary on past and present trends, and aids to improve the usability of re-ID techniques.<\/jats:p>","DOI":"10.1007\/s42979-024-03271-9","type":"journal-article","created":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T03:12:13Z","timestamp":1728270733000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Identifying Re-identification Challenges: Past, Current and Future Trends"],"prefix":"10.1007","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2418-6992","authenticated-orcid":false,"given":"Yan","family":"Qian","sequence":"first","affiliation":[]},{"given":"J.","family":"Barthelemy","sequence":"additional","affiliation":[]},{"given":"E.","family":"Karuppiah","sequence":"additional","affiliation":[]},{"given":"P.","family":"Perez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,7]]},"reference":[{"key":"3271_CR1","doi-asserted-by":"publisher","unstructured":"Ahmed E, Jones M, Marks TK. 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