Stacked Latent Attention for Multimodal Reasoning [CVPR 2018]
論文鏈接甩出來：點擊打開鏈接 堆疊潛在注意力模型：個人感覺這是一篇傳統Attention 和殘差網絡的拼接。。。 一. Standard Attention Mechanism Attention 實際上就是一個加權求和的過程。搞圖像的就突出圖像特徵而已。Attention map就是一張權值分佈圖，與feature map「點積」就是加權過程，關鍵是怎麼產生這張Attention map
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相關文章
- 1. 《Dual Attention Networks for Multimodal Reasoning and Matching》
- 2. CVPR 2018 paper
- 3. MUREL: Multimodal Relational Reasoning for Visual Question Answering筆記
- 4. 論文解讀：Dual Attention Networks for Multimodal Reasoning and Matching
- 5. 【論文閱讀】【CVPR2017】Dual Attention Networks for Multimodal Reasoning and Matching
- 6. 《Stacked Cross Attention for Image-Text Matching》
- 7. 論文筆記：Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering
- 8. 【ACL2020】Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
- 9. [CVPR 2018筆記] Discriminative Learning of Latent Features for Zero-Shot Recognition
- 10. [CVPR 2018]Discriminative Learning of Latent Features for Zero-Shot Recognition