{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automatic-building-extraction-in-aerial","title":"Automatic Building Extraction in Aerial Scenes Using Convolutional Networks","arxiv_id":"1602.06564","date":"2016-02-21","proceeding":null,"authors":["Jiangye Yuan"],"abstract":"Automatic building extraction from aerial and satellite imagery is highly\nchallenging due to extremely large variations of building appearances. To\nattack this problem, we design a convolutional network with a final stage that\nintegrates activations from multiple preceding stages for pixel-wise\nprediction, and introduce the signed distance function of building boundaries\nas the output representation, which has an enhanced representation power. We\nleverage abundant building footprint data available from geographic information\nsystems (GIS) to compile training data. The trained network achieves superior\nperformance on datasets that are significantly larger and more complex than\nthose used in prior work, demonstrating that the proposed method provides a\npromising and scalable solution for automating this labor-intensive task.","url_abs":"http://arxiv.org/abs/1602.06564v1","url_pdf":"http://arxiv.org/pdf/1602.06564v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"automatic-building-extraction-in-aerial","repo_url":"https://github.com/statisticalplumber/Building_detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1602.06564","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}