Batch DropBlock Network for Person Re-identification and Beyond
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
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- 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