基于深度学习的行人属性识别研究进展

X. Chen, Shanna Zhuang, Xueting Zheng, Zhengyou Wang
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引用次数: 0

摘要

随着智能视频监控的不断发展,行人属性的研究受到了广泛的关注。本文旨在介绍现有的基于深度学习的行人属性识别方法。总结了行人属性识别的研究现状。基于全局、基于局部、基于gcn和注意机制的深度学习行人属性识别研究。同时,介绍了行人属性识别的相关背景和概念。然后介绍了常用的数据集和评价标准。最后总结了当前的研究热点和未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pedestrian Attribute Recognition Based On Deep Learning : A Survey
With the continuous development of intelligent video surveillance, the research on pedestrian attributes has attracted widespread attention. The paper aims to introduce the existing pedestrian attribute recognition based on deep learning. We summarized the existing work on pedestrian attribute recognition. The research of deep learning on pedestrian attribute recognition in terms global-based, locally-based, of GCN-based and attention mechanisms. At the same time, we introduced the related background and concepts of pedestrian attribute recognition. Then, we introduced its commonly used datasets and evaluation criteria. At the end, we summarize the current research hotspots and future research directions.
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