【共生性】CVPR 2019:Multi-Label Image Recognition with Graph Convolutional Networks
通常來說，一個圖片裏的不同物體具有共生性，所以建模label dependencies可能提升識別性能。 爲了捕捉和探索這個重要的dependencies，本文作者提出了基於Graph Convolutional Network (GCN)的多標籤分類模型。 在object labels上構建一個有向圖，each node is represented by word embedding of a
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相關文章
- 1. Multi-Label Image Recognition with Graph Convolutional Networks
- 2. IMAGE DENOISING WITH GRAPH-CONVOLUTIONAL NEURAL NETWORKS
- 3. Multi-Label Image Recognition with Graph Convolutional Networks 論文筆記
- 4. 論文筆記：Multi-Label Image Recognition with Graph Convolutional Networks
- 5. 圖卷積：Multi-Label Image Recognition with Graph Convolutional Networks ∗
- 6. Multi-Label Image Recognition with Graph Convolutional Networks 論文閱讀筆記
- 7. 曠視2019CVPR-Multi-Label Image Recognition with Graph Convolutional Networks
- 8. 《Multi-Label Image Recognition with Graph Convolutional Networks》論文理解
- 9. Emotion Recognition Using Graph Convolutional Networks
- 10. Semi-Supervised Classification With Graph Convolutional Networks