Jiahe Wang1, Xizhan Gao1,*, Fa Zhu2, Xingchi Chen3
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 25-51, 2024, DOI:10.32604/cmc.2024.054895
- 15 October 2024
Abstract Video-based person re-identification (Re-ID), a subset of retrieval tasks, faces challenges like uncoordinated sample capturing, viewpoint variations, occlusions, cluttered backgrounds, and sequence uncertainties. Recent advancements in deep learning have significantly improved video-based person Re-ID, laying a solid foundation for further progress in the field. In order to enrich researchers’ insights into the latest research findings and prospective developments, we offer an extensive overview and meticulous analysis of contemporary video-based person Re-ID methodologies, with a specific emphasis on network architecture design and loss function design. Firstly, we introduce methods based on network architecture design and loss… More >
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