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In this paper, to remedy this deficiency, we propose a Linear AttentionMechanism which is approximate to dot-product attention with much less memoryand computational costs. The efficient design makes the incorporation betweenattention mechanisms and neural networks more flexible and versatile.Experiments conducted on semantic segmentation demonstrated the effectivenessof linear attention mechanism. Code is available athttps://github.com/lironui/Linear-Attention-Mechanism.

Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation