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2019 IET之ReID:HPILN: a feature learning framework for cross-modality person re-identification
時間 2020-12-30
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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.
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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
>>更多相關文章<<