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Smart city article details

Title	Person Re-Identification With Transformers And Image Stacking
ID_Doc	41892
Authors	Stojanovic D.; Pavkovic B.; Cetic N.
Year	2024
Published	2024 32nd Telecommunications Forum, TELFOR 2024 - Proceedings of Papers
DOI	http://dx.doi.org/10.1109/TELFOR63250.2024.10819135
Abstract	Person re-identification (ReID) is increasingly important due to the expansion of surveillance cameras. ReID can effectively operate in various conditions, making it suitable for security, retail analytics, and smart city applications. We propose a transformer-based model, DeepChangeVIT-ReID, fine-tuned with triplet loss, using the DeepChange dataset. We address long-term ReID challenges, including pose variations, camera angle differences, and clothing alterations. DeepChangeVIT-ReID achieves state-of-the-art performance, significantly improving Rank-1 accuracy compared to existing methods on the DeepChange dataset. © 2024 IEEE.
Author Keywords	Computer Vision; Image Processing; Person Re-identification; Surveillance Systems; Transformers

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