Unsupervised Person Re-identification: Clustering and Fine-tuning閱讀筆記
Unsupervised Person Re-identification: Clustering and Fine-tuning （PUL）閱讀筆記 How? 文字解釋就是： 現在源域上訓練一個CNN，然後到目標域對目標域圖像提特徵，特徵餵給KMeans聚類爲指定簇數(K)，對其中每簇中每個樣本特徵離中心樣本特徵的相似度(距離)，相似度大於閾值的保留，小於等於閾值的就剔除掉(噪聲，最終不會被採納，
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相關文章
- 1. Unsupervised Person Re-identification: Clustering and Fine-tuning
- 2. Unsupervised Person Re-identification: Clustering and Fine-tuning
- 3. Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification(CVPR2019)閱讀筆記
- 4. Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification閱讀筆記
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- 6. TOMM2018_Unsupervised Person Re-identification: Clustering and Fine-tuning
- 7. Clustering - Unsupervised learning introduction
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- 9. CVPR 2017 Multiple People Tracking by Lifted Multicut and Person Re-identification 閱讀筆記
- 10. 1604.Joint Detection and Identification Feature Learning for Person Search論文閱讀筆記