{"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/semantic-segmentation-using-adversarial","title":"Semantic Segmentation using Adversarial Networks","arxiv_id":"1611.08408","date":"2016-11-25","proceeding":null,"authors":["Pauline Luc","Camille Couprie","Soumith Chintala","Jakob Verbeek"],"abstract":"Adversarial training has been shown to produce state of the art results for\ngenerative image modeling. In this paper we propose an adversarial training\napproach to train semantic segmentation models. We train a convolutional\nsemantic segmentation network along with an adversarial network that\ndiscriminates segmentation maps coming either from the ground truth or from the\nsegmentation network. The motivation for our approach is that it can detect and\ncorrect higher-order inconsistencies between ground truth segmentation maps and\nthe ones produced by the segmentation net. Our experiments show that our\nadversarial training approach leads to improved accuracy on the Stanford\nBackground and PASCAL VOC 2012 datasets.","url_abs":"http://arxiv.org/abs/1611.08408v1","url_pdf":"http://arxiv.org/pdf/1611.08408v1.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":"semantic-segmentation-using-adversarial","repo_url":"https://github.com/ankit1997/implementing_papers","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1611.08408","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}