《MUTAN: Multimodal Tucker Fusion for Visual Question Answering》阅读笔记
《MUTAN: Multimodal Tucker Fusion for Visual Question Answering》阅读笔记 一、研究背景 Bilinear models在视觉问答（VQA）任务中进行信息融合提供了一个吸引人的框架。 它们有助于学习question meaning 和 visual concepts in the image之间的高层次关系，但它们存在高维度问题。 论文引
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相关文章
- 1. 《Visual Question Generation as Dual Task of Visual Question Answering》阅读笔记
- 2. MUREL: Multimodal Relational Reasoning for Visual Question Answering笔记
- 3. 阅读笔记（Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding)
- 4. Multimodal Encoder-Decoder Attention Networks for Visual Question Answering论文笔记
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- 7. 论文-《MUREL: Multimodal Relational Reasoning for Visual Question Answering Remi》重点翻译+扩展
- 8. Multi-level Attention Networks for Visual Question Answering阅读笔记
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