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Context-Gated Convolution
[article]
2020
arXiv
pre-print
As the basic building block of Convolutional Neural Networks (CNNs), the convolutional layer is designed to extract local patterns and lacks the ability to model global context in its nature. Many efforts have been recently devoted to complementing CNNs with the global modeling ability, especially by a family of works on global feature interaction. In these works, the global context information is incorporated into local features before they are fed into convolutional layers. However, research
arXiv:1910.05577v4
fatcat:6igeeru6yzcg3fgm444klrpdza