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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2025,4,30]]},"abstract":"<jats:p>\n            Current visible-infrared cross-modality person re-identification research has only focused on exploring the bi-modality mutual retrieval paradigm, and we propose a new and more practical mix-modality retrieval paradigm. Existing\n            <jats:bold>Visible-Infrared Person Re-Identification (VI-ReID)<\/jats:bold>\n            methods have achieved some results in the bi-modality mutual retrieval paradigm by learning the correspondence between visible and infrared modalities. However, significant performance degradation occurs due to the modality confusion problem when these methods are applied to the new mix-modality paradigm. Therefore, this article proposes a\n            <jats:bold>Mix-Modality Person Re-Identification (MM-ReID)<\/jats:bold>\n            task, explores the influence of modality mixing ratio on performance, and constructs mix-modality test sets for existing datasets according to the new mix-modality testing paradigm. To solve the modality confusion problem in MM-ReID, we propose a\n            <jats:bold>Cross-Identity Discrimination Harmonization Loss (CIDHL)<\/jats:bold>\n            adjusting the distribution of samples in the hyperspherical feature space, pulling the centers of samples with the same identity closer, and pushing away the centers of samples with different identities while aggregating samples with the same modality and the same identity. Furthermore, we propose a\n            <jats:bold>Modality Bridge Similarity Optimization Strategy (MBSOS)<\/jats:bold>\n            to optimize the cross-modality similarity between the query and queried samples with the help of the similar bridge sample in the gallery. Extensive experiments demonstrate that compared to the original performance of existing cross-modality methods on MM-ReID, the addition of our CIDHL and MBSOS demonstrates a general improvement.\n          <\/jats:p>","DOI":"10.1145\/3715142","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T15:53:42Z","timestamp":1738079622000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Mix-Modality Person Re-Identification: A New and Practical Paradigm"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6327-5780","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0748-3669","authenticated-orcid":false,"given":"Xin","family":"Xu","sequence":"additional","affiliation":[{"name":"Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan, China and School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6622-0645","authenticated-orcid":false,"given":"Hua","family":"Chang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3140-3243","authenticated-orcid":false,"given":"Xin","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3846-9157","authenticated-orcid":false,"given":"Zheng","family":"Wang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China"}]}],"member":"320","published-online":{"date-parts":[[2025,3,10]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"720","volume-title":"European Conference on Computer Vision","author":"Alehdaghi Mahdi","year":"2022","unstructured":"Mahdi Alehdaghi, Arthur Josi, Rafael M. 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