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Aug, 2017
无监督人物再识别的跨视角非对称度量学习
Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification
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Hong-Xing Yu, Ancong Wu, Wei-Shi Zheng
TL;DR
该研究提出了一种基于不对称聚类的度量学习方法,通过学习对称性,提高无人监督条件下,在大规模无标签视觉数据下的RE-ID的匹配性能,实验结果表明,该方法比传统的无人监督方法更为适用。
Abstract
While
metric learning
is important for Person re-identification (RE-ID), a significant problem in visual surveillance for
cross-view pedestrian matching
, existing metric models for RE-ID are mostly based on super
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