Methods › Computer Vision › Image Model Blocks › Efficient Channel Attention
Efficient Channel Attention
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
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 k neighbors. The ECA can be efficiently implemented by fast 1D convolution of size k, where kernel size k represents the coverage of local cross-channel interaction, i.e., how many neighbors participate in attention prediction of one channel.
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