Multi-level Attention Networks for Visual Question Answering閱讀筆記
Multi-level Attention Networks 這個模型可以同時提取高級語義信息和空間信息，模型框架如下所示： 該模型分爲三個部分，分別是Semantic Attention、Context-aware Visual Attention、Joint Attention Learning。 Semantic Attention 語義注意的工作是從圖像中挖掘重要的概念來回答問題。雖然概念
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相關文章
- 1. 《Multi-level Attention Networks for Visual Question Answering》閱讀筆記
- 2. Stacked Attention Networks for Image Question Answering閱讀筆記
- 3. Question-Guided Spatio-Temporal Contextual Attention for Video Question Answering 論文閱讀筆記
- 4. 閱讀筆記（Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding)
- 5. Multimodal Encoder-Decoder Attention Networks for Visual Question Answering論文筆記
- 6. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記
- 7. Cycle-Consistency for Robust Visual Question Answering閱讀筆記
- 8. A Context-aware Attention Network for Interactive Question Answering--閱讀筆記
- 9. 《Visual Question Generation as Dual Task of Visual Question Answering》閱讀筆記
- 10. Visual Question Answering with Memory-Augmented Networks