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ICCV2019-行人重识别-Mixed High-Order Attention Network for Person Re-Identification
时间 2021-01-07
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动机: 依旧是一篇基于attention 的论文,不得不说现在market数据集上top10基本被attention霸榜了。这篇文章的出发点和SONA很类似,作者分析目前attention的操作都太过于粗糙,例如 spatial attention 和 channel attention ,需要高阶的操作以获取更多local之间的关系。 创新: 乍一看first-order和channel att
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相关文章
1.
[行人重识别]--ICCV2019-Mixed High-Order Attention Network for Person Re-Identification
2.
ICCV2019-行人重识别-Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
3.
ICCV2019-行人重识别-View Confusion Feature Learning for Person Re-identification
4.
CVPR2019-行人重识别-Interaction-and-Aggregation Network for Person Re-identification
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Collaborative Attention Network for Person Re-identification
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Harmonious Attention Network for Person Re-Identification
8.
[行人重识别]--AAAI2020-Relation Network for Person Re-identification
9.
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行人再识别:Mask-guided Contrastive Attention Model for Person Re-Identification
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