{"url":"/method/bilateral-guided-aggregation-layer","slug":"bilateral-guided-aggregation-layer","name":"Bilateral Guided Aggregation Layer","full_name":"Bilateral Guided Aggregation Layer","full_name_withheld":false,"description_markdown":"**Bilateral Guided Aggregation Layer** is a feature fusion layer for semantic segmentation that aims to enhance mutual connections and fuse different types of feature representation. It was used in the [BiSeNet V2](https://paperswithcode.com/method/bisenet-v2) architecture. Specifically, within the BiSeNet implementation, the layer was used to employ the contextual information of the Semantic Branch to guide the feature response of Detail Branch. With different scale guidance, different scale feature representations can be captured, which inherently encodes the multi-scale information.","description_state":"present","introduced_year":null,"introduced_by":{"title":"BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation","paper":"/paper/bisenet-v2-bilateral-network-with-guided","first_author":"Changqian Yu","n_authors":6,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/bisenet-v2-bilateral-network-with-guided"},"source":{"url":"https://arxiv.org/abs/2004.02147v1","title":"BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Semantic Segmentation Modules","url":"/methods/category/semantic-segmentation-modules","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":null,"title":"Exploring Lip Segmentation Techniques in Computer Vision: A Comparative Analysis","date":"2023-11-20","arxiv_id":"2311.11992","n_code_links":0,"syntology":null},{"paper":"/paper/bisenet-v2-bilateral-network-with-guided","title":"BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation","date":"2020-04-05","arxiv_id":"2004.02147","n_code_links":7,"syntology":{"ran":6,"of":10,"unverified":4,"pointer_only":5}}],"papers_shown":2,"tasks":[{"task":"/task/segmentation","name":"Segmentation","papers":2},{"task":"/task/edge-computing","name":"Edge-computing","papers":1},{"task":"/task/lip-reading","name":"Lip Reading","papers":1},{"task":"/task/real-time-semantic-segmentation","name":"Real-Time Semantic Segmentation","papers":1},{"task":"/task/semantic-segmentation","name":"Semantic Segmentation","papers":1}],"tasks_shown":5,"n_tasks":5,"usage_by_year":[{"year":"2020","papers":1},{"year":"2023","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/bilateral-guided-aggregation-layer"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}