2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
HPILN: a feature learning framework for cross-modality person re-identification 當前的問題及概述： 提出了一種新的特徵學習框架：hard pentaplet loss和identity loss network (HPILN),(HPILN)。在該框架中，對現有的單模態再識別模型進行了修正以適應交叉模態場景，並採用專門
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相關文章
- 1. View Confusion Feature Learning for Person Re-identification
- 2. [CVPR 2019] f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning
- 3. 【KDD 2019】A Representation Learning Framework for Property Graphs
- 4. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 5. 2019 CVPR：Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
- 6. Person search: Joint Detection and Identification Feature Learning for Person Search筆記
- 7. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
- 8. Learning Context Graph for Person Search
- 9. Paper Reading: f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning
- 10. 19ArXiv之ReID：Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person