(JGSA) Joint Geometrical and Statistical Alignment for Visual Domain Adaptation
2017 CVPR 官方代碼：https://www.uow.edu.au/~jz960/ 讀完，感覺以下兩點思想感覺和2018年的DICD有點相似之處： the variance of target domain is maximized, the discriminative information of source domain is preserved 但是DICD考慮的是作域變換之後數
相關文章
- 1. [cvpr2017]Joint Geometrical and Statistical Alignment for Visual Domain Adaptation
- 2. Deep CORAL: Correlation Alignment for Deep Domain Adaptation（2016）
- 3. Deep CORAL: Correlation Alignment for Deep Domain Adaptation
- 4. Domain Adaptation總結（2017.9）
- 5. 筆記：Domain Adaptation on the Statistical Manifold
- 6. 【論文整理】深度學習Domain-Adaptation領域遷移最全論文列表！
- 7. 域適應學習筆記：visual Domain Adaptation
- 8. Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
- 9. Deep visual domain adaptation: A survey
- 10. 論文筆記：Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
- 更多相關文章...
- • Swift for 循環 - Swift 教程
- • Scala for循環 - Scala教程
- • RxJava操作符（七）Conditional and Boolean
- • 算法總結-股票買賣
相關標籤/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。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. [cvpr2017]Joint Geometrical and Statistical Alignment for Visual Domain Adaptation
- 2. Deep CORAL: Correlation Alignment for Deep Domain Adaptation（2016）
- 3. Deep CORAL: Correlation Alignment for Deep Domain Adaptation
- 4. Domain Adaptation總結（2017.9）
- 5. 筆記：Domain Adaptation on the Statistical Manifold
- 6. 【論文整理】深度學習Domain-Adaptation領域遷移最全論文列表！
- 7. 域適應學習筆記：visual Domain Adaptation
- 8. Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation
- 9. Deep visual domain adaptation: A survey
- 10. 論文筆記：Cluster Alignment with a Teacher for Unsupervised Domain Adaptation