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Attention Analysis in Caption Generation

机译:字幕生成中的注意力分析

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摘要

Caption Generation is one of the fundamental tasks combining computer vision and natural language processing. To achieve this goal, neural networks are employed to implement a caption generation system. In this paper, we proposed a caption generation system combining a CNN-based object detection system and a language model with a recurrent neural network. Especially, a vector which is sent from the object detection system to the language model is generated using an attention mechanism. Attention visualization can help us to understand the system focuses on a part of the input image in generating a caption. In the experiments, we evaluate the performance of the proposed system and discuss the effects of the attention mechanism in the image caption. Especially, the attention contributes to the improvement of caption generation but the attention is uncorrelated to system interpretation.
机译:字幕生成是将计算机视觉和自然语言处理相结合的基本任务之一。为了实现这一目标,采用了神经网络来实现字幕生成系统。在本文中,我们提出了一种结合了基于CNN的目标检测系统和语言模型以及递归神经网络的字幕生成系统。特别地,使用注意力机制生成从对象检测系统发送到语言模型的向量。注意可视化可以帮助我们理解系统在生成标题时将重点放在输入图像的一部分上。在实验中,我们评估了所提出系统的性能,并讨论了注意机制在图像标题中的作用。特别是,注意力有助于字幕生成的改善,但注意力与系统解释无关。

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