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ICCV2019-行人重識別-Mixed High-Order Attention Network for Person Re-Identification
時間 2021-01-07
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動機: 依舊是一篇基於attention 的論文,不得不說現在market數據集上top10基本被attention霸榜了。這篇文章的出發點和SONA很類似,作者分析目前attention的操作都太過於粗糙,例如 spatial attention 和 channel attention ,需要高階的操作以獲取更多local之間的關係。 創新: 乍一看first-order和channel att
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相關文章
1.
[行人重識別]--ICCV2019-Mixed High-Order Attention Network for Person Re-Identification
2.
ICCV2019-行人重識別-Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
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4.
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ICCV2019-行人重識別-Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
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Collaborative Attention Network for Person Re-identification
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[行人重識別]--AAAI2020-Relation Network for Person Re-identification
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行人再識別:Mask-guided Contrastive Attention Model for Person Re-Identification
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