{"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/dsm-building-shape-refinement-from-combined","title":"DSM Building Shape Refinement from Combined Remote Sensing Images based on Wnet-cGANs","arxiv_id":"1903.03519","date":"2019-03-08","proceeding":null,"authors":["Ksenia Bittner","Marco Körner","Peter Reinartz"],"abstract":"We describe the workflow of a digital surface models (DSMs) refinement\nalgorithm using a hybrid conditional generative adversarial network (cGAN)\nwhere the generative part consists of two parallel networks merged at the last\nstage forming a WNet architecture. The inputs to the so-called WNet-cGAN are\nstereo DSMs and panchromatic (PAN) half-meter resolution satellite images.\nFusing these helps to propagate fine detailed information from a spectral image\nand complete the missing 3D knowledge from a stereo DSM about building shapes.\nBesides, it refines the building outlines and edges making them more\nrectangular and sharp.","url_abs":"http://arxiv.org/abs/1903.03519v1","url_pdf":"http://arxiv.org/pdf/1903.03519v1.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":"dsm-building-shape-refinement-from-combined","repo_url":"https://github.com/0xzayd/Wnet-cGAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}