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 一般来说，在训练基于度量的网络的时候，使用的triple Loss要优先于其他，随着数据集合Market-1501以
相关文章
- 1. 1703.In Defense of the Triplet Loss for Person Re-Identification 论文阅读笔记
- 2. 【行人重识别】《In Defense of the Triplet Loss for Person Re-Identification》论文阅读
- 3. In-depth exploration of attribute information for person re-identification
- 4. Triplet Loss入门
- 5. Protect the self: defense mechanisms in action
- 6. triplet loss
- 7. 行人再识别：Beyond triplet loss: a deep quadruplet network for person re-identification
- 8. [论文笔记]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
- 更多相关文章...
- • Swift for-in 循环 - Swift 教程
- • Scala for循环 - Scala教程
- • Java 8 Stream 教程
- • 为了进字节跳动，我精选了29道Java经典算法题，带详细讲解
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 1703.In Defense of the Triplet Loss for Person Re-Identification 论文阅读笔记
- 2. 【行人重识别】《In Defense of the Triplet Loss for Person Re-Identification》论文阅读
- 3. In-depth exploration of attribute information for person re-identification
- 4. Triplet Loss入门
- 5. Protect the self: defense mechanisms in action
- 6. triplet loss
- 7. 行人再识别：Beyond triplet loss: a deep quadruplet network for person re-identification
- 8. [论文笔记]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