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Batch DropBlock Network for Person Re-identification and Beyond
時間 2021-01-03
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Batch DropBlock Network for Person Re-identification and Beyond 摘要 重識別問題的難點主要在於姿態的多變,隨機遮擋等會降低模型的精度,本文提出了一個BDB的網絡,主要有兩個分支,一個是主分支是resnet50網絡,另一個是drop分支。Drop分支主要是爲了抽取局部關注點信息,隨機的去除batch中輸入feature ma
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相關文章
1.
【ReID】Batch DropBlock Network for Person Re-identification and Beyond
2.
Batch DropBlock Network for Person Re-identification and Beyond論文閱讀
3.
論文閱讀 Batch DropBlock Network for Person Re-identification and Beyond
4.
Batch Drop Block Network for Person Re-identification and Beyond
5.
【論文閱讀】Batch Feature Erasing for Person Re-identification and Beyond
6.
【論文閱讀】Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
7.
行人再識別:Beyond triplet loss: a deep quadruplet network for person re-identification
8.
AOD-NET:An All-in-One Network for Dehazing and Beyond
9.
2019CVPR之ReID:Interaction-and-Aggregation Network for Person Re-identification
10.
1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
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