Author(s)

Mingda Yang ¹, Wenzhun Huang ¹, Ruixiang Li ¹, Chengyu Hu ¹

Affiliation(s)

¹ School of Electronic Information, Xijing University, Xi'an, China

Corresponding Author

Wenzhun Huang

ABSTRACT

Pedestrian re-identification is dedicated to recognizing the same individual across different cameras and fields of view. With the development of deep learning methodologies and computational capabilities, deep learning and related approaches have been widely applied in the research domain of pedestrian re-identification. By summarizing the latest advancements in the application of deep learning to pedestrian re-identification, this paper categorizes the research of scholars both domestically and internationally in recent years. It analyzes different algorithms, datasets, and performance evaluation metrics, compares the strengths and weaknesses of various methods, and thereby points out current research hotspots and the broad prospects for future development.

KEYWORDS

Pedestrian Re-identification, Deep Learning, Convolutional Neural Networks, Attention Mechanisms

CITE THIS PAPER

Mingda Yang, Wenzhun Huang, Ruixiang Li, Chengyu Hu, Review of Deep Learning-based Pedestrian Re-identification Research. Automation and Machine Learning (2024) Vol. 5: 104-112. DOI: http://dx.doi.org/10.23977/autml.2024.050113.

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