Stacked Latent Attention for Multimodal Reasoning [CVPR 2018]

时间 2021-01-09

标签注意力机制 attention model 繁體版

原文原文链接

论文链接甩出来：点击打开链接堆叠潜在注意力模型：个人感觉这是一篇传统Attention 和残差网络的拼接。。。一. Standard Attention Mechanism Attention 实际上就是一个加权求和的过程。搞图像的就突出图像特征而已。Attention map就是一张权值分布图，与feature map“点积”就是加权过程，关键是怎么产生这张Attention map

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1. 《Dual Attention Networks for Multimodal Reasoning and Matching》
2. CVPR 2018 paper
3. MUREL: Multimodal Relational Reasoning for Visual Question Answering笔记
4. 论文解读：Dual Attention Networks for Multimodal Reasoning and Matching
5. 【论文阅读】【CVPR2017】Dual Attention Networks for Multimodal Reasoning and Matching
6. 《Stacked Cross Attention for Image-Text Matching》
7. 论文笔记：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笔记] Discriminative Learning of Latent Features for Zero-Shot Recognition
10. [CVPR 2018]Discriminative Learning of Latent Features for Zero-Shot Recognition
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1. 《Dual Attention Networks for Multimodal Reasoning and Matching》
2. CVPR 2018 paper
3. MUREL: Multimodal Relational Reasoning for Visual Question Answering笔记
4. 论文解读：Dual Attention Networks for Multimodal Reasoning and Matching
5. 【论文阅读】【CVPR2017】Dual Attention Networks for Multimodal Reasoning and Matching
6. 《Stacked Cross Attention for Image-Text Matching》
7. 论文笔记：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笔记] Discriminative Learning of Latent Features for Zero-Shot Recognition
10. [CVPR 2018]Discriminative Learning of Latent Features for Zero-Shot Recognition

>>更多相关文章<<