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Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
時間 2020-12-29
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剛剛看完這篇論文,整理了一下思路。這篇論文基於神經元在學習不同特徵時活躍程度不同而提出DGD的方法,也是666的 論文:https://arxiv.org/abs/1604.07528 代碼:https://github.com/Cysu/dgd_person_reid 論文解析 文章一開始,作者解釋了爲什麼要使用多個數據集進行訓練: Learning generic and robust fea
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相關文章
1.
1604. Learning deep feature representations with domain guided dropout for re-id論文閱讀筆記
2.
1604.An Enhanced Deep Feature Representation for Person Re-identification 論文筆記
3.
1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
4.
【ReID】Hierarchical and Efficient Learning for Person Re-Identification
5.
【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
6.
part-aligned系列論文:1707.Deep Representation Learning with Part Loss for Person ReID 論文閱讀筆記
7.
【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8.
View Confusion Feature Learning for Person Re-identification
9.
2019 IET之ReID:HPILN: a feature learning framework for cross-modality person re-identification
10.
Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
>>更多相關文章<<