【论文阅读】【CVPR2017】Dual Attention Networks for Multimodal Reasoning and Matching
Abstract 我们提出双重注意网络模型（DANs）利用视觉和文字共同注意机制捕捉视觉和语言之间的细微互动。 DANs关注图像和文字的特定区域文本信息，这些文本信息是通过多个步骤收集来自两种模式的重要信息。 基于这个框架，我们引入两种类型的DANs进行多模态推理,匹配以及分类。 推理模型允许可视化并在协作推理期间用文本注意机制互相关联，这对于视觉问答（VQA）等任务很有用。 此外，匹配模型利用文
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相关文章
- 1. 《Dual Attention Networks for Multimodal Reasoning and Matching》
- 2. 论文解读：Dual Attention Networks for Multimodal Reasoning and Matching
- 3. 论文《Matching Networks for One Shot Learning》阅读
- 4. Gated Self-Matching Networks for Reading Comprehension and Question Answering论文阅读笔记
- 5. 论文阅读 | Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction
- 6. 【论文阅读】Further Non-local and Channel Attention Networks for Vehicle Re-identification
- 7. 文章阅读：Dual Attention Network for Scene Segmentation
- 8. 【论文阅读】【CVPR2017】Temporal Attention-Gated Model for Robust Sequence Classification
- 9. Stacked Latent Attention for Multimodal Reasoning [CVPR 2018]
- 10. Dual Attention Network for Scene Segmentation论文阅读&翻译