Research of Self-Attention in Image Segmentation

Fude Cao, Chunguang Zheng, Limin Huang, Aihua Wang, Jiong Zhang, Feng Zhou, Haoxue Ju, Haitao Guo, Yuxia Du
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引用次数: 1

Abstract

Although the traditional convolutional neural network is applied to image segmentation successfully, it has some limitations. That's the context information of the long-range on the image is not well captured. With the success of the introduction of self-attentional mechanisms in the field of natural language processing (NLP), people have tried to introduce the attention mechanism in the field of computer vision. It turns out that self-attention can really solve this long-range dependency problem. This paper is a summary on the application of self-attention to image segmentation in the past two years. And think about whether the self-attention module in this field can replace convolution operation in the future.
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图像分割中自注意的研究
传统的卷积神经网络虽然在图像分割中得到了成功的应用,但存在一定的局限性。这就是图像上远距离的背景信息没有被很好地捕捉到。随着自注意机制在自然语言处理(NLP)领域的成功引入,人们开始尝试在计算机视觉领域引入注意机制。事实证明,自我关注确实可以解决这种长期依赖问题。本文对近两年来自关注在图像分割中的应用进行了综述。并思考该领域的自注意模块能否在未来取代卷积运算。
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