{"url":"/method/efficient-channel-attention","slug":"efficient-channel-attention","name":"Efficient Channel Attention","full_name":"Efficient Channel Attention","full_name_withheld":false,"description_markdown":"**Efficient Channel Attention** is an architectural unit based on [squeeze-and-excitation](https://paperswithcode.com/method/squeeze-and-excitation-block) blocks that reduces model complexity without dimensionality reduction. It was proposed as part of the [ECA-Net](https://paperswithcode.com/method/eca-net) CNN architecture. \r\n\r\nAfter channel-wise [global average pooling](https://paperswithcode.com/method/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](https://paperswithcode.com/method/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.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/1910.03151v4","title":"ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/BangguWu/ECANet/blob/cf8a4c8b3d49b27c12e98ceb930d0f7db6c2460a/models/eca_module.py#L5","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Image Model Blocks","url":"/methods/category/image-model-blocks","pwc_aliases":[]}],"n_papers_tagged":0,"archive_num_papers":null,"papers_newest_first":[],"papers_shown":0,"tasks":[],"tasks_shown":0,"n_tasks":0,"usage_by_year":[],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/efficient-channel-attention"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}