【論文閱讀】【CVPR2017】Dual Attention Networks for Multimodal Reasoning and Matching
Abstract 我們提出雙重注意網絡模型（DANs）利用視覺和文字共同注意機制捕捉視覺和語言之間的細微互動。 DANs關注圖像和文字的特定區域文本信息，這些文本信息是通過多個步驟收集來自兩種模式的重要信息。 基於這個框架，我們引入兩種類型的DANs進行多模態推理,匹配以及分類。 推理模型允許可視化並在協作推理期間用文本注意機制互相關聯，這對於視覺問答（VQA）等任務很有用。 此外，匹配模型利用文
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相關文章
- 1. 《Dual Attention Networks for Multimodal Reasoning and Matching》
- 2. 論文解讀：Dual Attention Networks for Multimodal Reasoning and Matching
- 3. 論文《Matching Networks for One Shot Learning》閱讀
- 4. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記
- 5. 論文閱讀 | Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction
- 6. 【論文閱讀】Further Non-local and Channel Attention Networks for Vehicle Re-identification
- 7. 文章閱讀：Dual Attention Network for Scene Segmentation
- 8. 【論文閱讀】【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論文閱讀&翻譯