论文笔记：Attention Correctness in Neural Image Captioning
Attention Correctness in Neural Image Captioning 这篇论文在attention上做足了文章，分别建立了一个有监督attention训练机制，和新的评价标准，Attention Correctness。 Supervised attention model 在attention机制中，是以 来表示t时刻在视觉块a上的关注度，具体如下。 在这个参数的
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相关文章
- 1. 论文笔记：Areas of Attention for Image Captioning
- 2. 论文笔记：Image Captioning with Semantic Attention
- 3. 论文笔记：X-Linear Attention Networks for Image Captioning
- 4. 论文笔记：Reference based LSTM for Image Captioning
- 5. 论文笔记：Contrastive Learning for Image Captioning
- 6. Exploring Visual Relationship for Image Captioning论文笔记
- 7. Image Captioning with Semantic Attention
- 8. 论文笔记：Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
- 9. 【论文笔记】Reasoning about Entailment with Neural Attention
- 10. 【论文笔记】(HEVC)《Multi-stage Attention Convolutional Neural Networks for HEVC In-Loop Filtering》