《Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for VQA》读后感想
跟随attetion工作阅读该文 摘要 该文给我带来的思考首先于注意力的使用，它采用的co-attention结构，注意力函数类似于attention is all you need 类似采用多层尺度乘法注意，第二它采用拉伸的特征向量表示句子或图像。 模型结构 如图所示，Q 和V分别是图像和问句的特征表示，大小为d×T， d×N，T 为特征图展平后长度，N为句子长度。该模型共有L个堆叠的Dense
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相关文章
- 1. Visual Genome ：Connecting Language and Vision Using Crowdsourced Dense Image Annotations.
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- 4. PROGRESSIVE GROWING OF GANs for IMPROVED QUALITY, STABILITY AND VARIATION
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