Deep Image Retrieval: Learning global representations for image search
Deep Image Retrieval: Learning global representations for image search 文中貢獻 學習特徵權重，構建區域特徵。 2. 使用區域推薦網絡，學習哪個區域需要細化形成池化構建成全局表達 文中使用三流孿生網絡，優化R-MAC向量權重。通過使用triplet ranking loss。 第二個貢獻是學習R-MAC pooling機制。
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相關文章
- 1. Deep Image Retrieval: Learning GlobalRepresentations for Image Search
- 2. End-to-End Learning of Deep Visual Representations for Image Retrieval
- 3. Deep Supervised Hashing for Fast Image Retrieval
- 4. Deep Residual Learning for Image Recognition
- 5. Binary Code for Image Search
- 6. Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval
- 7. Deep Hash in Large Scale Image Retrieval
- 8. Deep Learning for Information Retrieval
- 9. Deep Residual Learning For Image Recognition
- 10. Hierarchical deep semantic hashing for fast image retrieval