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Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation (2007.14902v3)

Published 29 Jul 2020 in cs.CV

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

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Authors (4)
  1. Rui Li (384 papers)
  2. Jianlin Su (31 papers)
  3. Chenxi Duan (15 papers)
  4. Shunyi Zheng (8 papers)
Citations (30)

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