2019 CVPR：Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification 當前的問題及概述： 雖然針對差異性局部特徵對ReID任務是有效的，但它們僅限於成對的被標記數據大間隙上進行訓練，但在其他小間隙的不相似部分獲取起來成本較大。如下圖： 本文提出了一個基於patch的無監督學習框架來克服這個問題，以
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相關文章
- 1. 【論文閱讀】 Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
- 2. 【論文筆記】Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
- 3. Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification(CVPR2019)閱讀筆記
- 4. [CVPR2019]Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification論文筆記
- 5. 19ArXiv之ReID：Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person
- 6. Joint Discriminative and Generative Learning for Person Re-identification
- 7. 【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
- 8. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
- 9. 18-Learning-a-Discriminative-Feature-Network-for-Semantic-Segmentation
- 10. A Discriminative Feature Learning Approach for Deep Face Recognition