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What is: Efficient Channel Attention?

SourceECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

Efficient Channel Attention is an architectural unit based on squeeze-and-excitation blocks that reduces model complexity without dimensionality reduction. It was proposed as part of the ECA-Net CNN architecture.

After channel-wise global average pooling without dimensionality reduction, the ECA captures local cross-channel interaction by considering every channel and its kk neighbors. The ECA can be efficiently implemented by fast 1D1D convolution of size kk, where kernel size kk represents the coverage of local cross-channel interaction, i.e., how many neighbors participate in attention prediction of one channel.