Open Access

REVIEW

Review of GAN-Based Person Re-Identification

Zhiyuan Luo^*

School of Computer & Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

* Corresponding Author: Zhiyuan Luo. Email:

Journal of New Media 2021, 3(1), 11-17. https://doi.org/10.32604/jnm.2021.018027

Received 22 February 2021; Accepted 02 March 2021; Issue published 15 March 2021

Abstract

Person re-ID is becoming increasingly popular in the field of modern surveillance. The purpose of person re-ID is to retrieve person of interests in non-overlapping multi-camera surveillance system. Due to the complexity of the surveillance scene, the person images captured by cameras often have problems such as size variation, rotation, occlusion, illumination difference, etc., which brings great challenges to the study of person re-ID. In recent years, studies based on deep learning have achieved great success in person re-ID. The improvement of basic networks and a large number of studies on the influencing factors have greatly improved the accuracy of person re-ID. Recently, some studies utilize GAN to tackle the domain adaptation task by transferring person images of source domain to the style of target domain and have achieved state of the art result in person re-ID.

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Keywords

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