{"url":"/method/corner-pooling","slug":"corner-pooling","name":"Corner Pooling","full_name":"Corner Pooling","full_name_withheld":false,"description_markdown":"**Corner Pooling** is a pooling technique for object detection that seeks to better localize corners by encoding explicit prior knowledge. Suppose we want to determine if a pixel at location $\\left(i, j\\right)$ is a top-left corner. Let $f\\_{t}$ and $f\\_{l}$ be the feature maps that are the inputs to the top-left corner pooling layer, and let $f\\_{t\\_{ij}}$ and $f\\_{l\\_{ij}}$ be the vectors at location $\\left(i, j\\right)$ in $f\\_{t}$ and $f\\_{l}$ respectively. With $H \\times W$ feature maps, the corner pooling layer first max-pools all feature vectors between $\\left(i, j\\right)$ and $\\left(i, H\\right)$ in $f\\_{t}$ to a feature vector $t\\_{ij}$ , and max-pools all feature vectors between $\\left(i, j\\right)$ and $\\left(W, j\\right)$ in $f\\_{l}$ to a feature vector $l\\_{ij}$. Finally, it adds $t\\_{ij}$ and $l\\_{ij}$ together.","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":"http://arxiv.org/abs/1808.01244v2","title":"CornerNet: Detecting Objects as Paired Keypoints","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/princeton-vl/CornerNet/blob/0017821eb0e127918dfd29a1a5976558babb582d/models/CornerNet.py#L7","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Pooling Operations","url":"/methods/category/pooling-operations","pwc_aliases":["pooling-operation"]}],"n_papers_tagged":12,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"SpaDen : Sparse and Dense Keypoint Estimation for Real-World Chart Understanding","date":"2023-08-03","arxiv_id":"2308.01971","n_code_links":0,"syntology":null},{"paper":null,"title":"CA-CentripetalNet: A novel anchor-free deep learning framework for hardhat wearing detection","date":"2023-07-09","arxiv_id":"2307.04103","n_code_links":0,"syntology":null},{"paper":"/paper/robust-table-detection-and-structure","title":"Robust Table Detection and Structure Recognition from Heterogeneous Document Images","date":"2022-03-17","arxiv_id":"2203.09056","n_code_links":0,"syntology":null},{"paper":null,"title":"TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Cases","date":"2021-04-19","arxiv_id":"2104.09123","n_code_links":0,"syntology":null},{"paper":"/paper/siamcorners-siamese-corner-networks-for","title":"SiamCorners: Siamese Corner Networks for Visual Tracking","date":"2021-04-15","arxiv_id":"2104.07303","n_code_links":1,"syntology":null},{"paper":"/paper/relationnet-bridging-visual-representations","title":"RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder","date":"2020-10-29","arxiv_id":"2010.15831","n_code_links":4,"syntology":{"ran":0,"of":5,"unverified":5,"pointer_only":0}},{"paper":"/paper/centripetalnet-pursuing-high-quality-keypoint","title":"CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection","date":"2020-03-20","arxiv_id":"2003.09119","n_code_links":2,"syntology":null},{"paper":"/paper/matrixnets-a-new-scale-and-aspect-ratio-aware","title":"MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection","date":"2020-01-09","arxiv_id":"2001.03194","n_code_links":1,"syntology":null},{"paper":"/paper/190408900","title":"CornerNet-Lite: Efficient Keypoint Based Object Detection","date":"2019-04-18","arxiv_id":"1904.08900","n_code_links":6,"syntology":{"ran":1,"of":27,"unverified":26,"pointer_only":0}},{"paper":"/paper/centernet-object-detection-with-keypoint","title":"CenterNet: Keypoint Triplets for Object Detection","date":"2019-04-17","arxiv_id":"1904.08189","n_code_links":20,"syntology":{"ran":2,"of":11,"unverified":9,"pointer_only":2}},{"paper":"/paper/bottom-up-object-detection-by-grouping","title":"Bottom-up Object Detection by Grouping Extreme and Center Points","date":"2019-01-23","arxiv_id":"1901.08043","n_code_links":2,"syntology":{"ran":1,"of":5,"unverified":4,"pointer_only":0}},{"paper":"/paper/cornernet-detecting-objects-as-paired","title":"CornerNet: Detecting Objects as Paired Keypoints","date":"2018-08-03","arxiv_id":"1808.01244","n_code_links":5,"syntology":{"ran":3,"of":11,"unverified":8,"pointer_only":0}}],"papers_shown":12,"tasks":[{"task":"/task/object-detection","name":"Object Detection","papers":8},{"task":"/task/object-detection-1","name":"object-detection","papers":8},{"task":"/task/object","name":"Object","papers":7},{"task":"/task/keypoint-estimation","name":"Keypoint Estimation","papers":2},{"task":"/task/region-proposal","name":"Region Proposal","papers":2},{"task":"/task/chart-understanding","name":"Chart Understanding","papers":1},{"task":"/task/decoder","name":"Decoder","papers":1},{"task":"/task/deep-learning","name":"Deep Learning","papers":1},{"task":"/task/instance-segmentation","name":"Instance Segmentation","papers":1},{"task":"/task/management","name":"Management","papers":1},{"task":"/task/metric-learning","name":"Metric Learning","papers":1},{"task":null,"name":"Position","papers":1},{"task":"/task/real-time-object-detection","name":"Real-Time Object Detection","papers":1},{"task":"/task/semantic-segmentation","name":"Semantic Segmentation","papers":1},{"task":"/task/table-detection","name":"Table Detection","papers":1},{"task":"/task/table-recognition","name":"Table Recognition","papers":1},{"task":null,"name":"Triplet","papers":1},{"task":"/task/visual-tracking","name":"Visual Tracking","papers":1},{"task":"/task/high","name":"Vocal Bursts Intensity Prediction","papers":1}],"tasks_shown":19,"n_tasks":19,"usage_by_year":[{"year":"2018","papers":1},{"year":"2019","papers":3},{"year":"2020","papers":3},{"year":"2021","papers":2},{"year":"2022","papers":1},{"year":"2023","papers":2}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/corner-pooling"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}