In Defense of the Triplet Loss for Person Re-Identification
In Defense of the Triplet Loss for Person Re-Identification Git地址： https:// github.com/VisualComputingInstitute/triplet-reid 框架 theano 摘要 一般來說，在訓練基於度量的網絡的時候，使用的triple Loss要優先於其他，隨着數據集合Market-1501以
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- 3. In-depth exploration of attribute information for person re-identification
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- 5. Protect the self: defense mechanisms in action
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相關文章
- 1. 1703.In Defense of the Triplet Loss for Person Re-Identification 論文閱讀筆記
- 2. 【行人重識別】《In Defense of the Triplet Loss for Person Re-Identification》論文閱讀
- 3. In-depth exploration of attribute information for person re-identification
- 4. Triplet Loss入門
- 5. Protect the self: defense mechanisms in action
- 6. triplet loss
- 7. 行人再識別：Beyond triplet loss: a deep quadruplet network for person re-identification
- 8. [論文筆記]Modeling Inter and Intra-Class Relations in the Triplet Loss for Zero-Shot Learning
- 9. Triplet Loss, Ranking Loss, Margin Loss
- 10. Facenet Triplet Loss