Aggregating Deep Convolutional Features for Image Retrieval閱讀筆記
CVPR2016 圖像檢索論文閱讀筆記 最經由於工作需要閱讀了這篇論文 文中主要工作提出了SPoC機制 一、首先討論了每層卷積層的特徵和sift等特徵的在圖像檢索的表徵能力 作者採用conv5（VGG） 二、SPoC design 1、Sum pooling. 假設我們卷積出來的特徵爲B*C*H*W維的矩陣，首先在每個h*w的feature map 上進行求和 2、Centering prior.
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相關文章
- 1. Content-based image retrieval with compact deep convolutional features
- 2. FUSING DEEP LOCAL AND GLOBAL FEATURES FOR REMOTE SENSING IMAGE SCENE CLASSIFICATION閱讀筆記
- 3. Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval 論文筆記
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- 6. 論文閱讀筆記--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 7. Deep Residual Learning for Image Recognition閱讀筆記
- 8. 論文閱讀筆記：Learning Deep Features for Discriminative Localization
- 9. Deep Image Prior 閱讀筆記
- 10. Deep image prior閱讀筆記