{"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/active-decision-boundary-annotation-with-deep","title":"Active Decision Boundary Annotation with Deep Generative Models","arxiv_id":"1703.06971","date":"2017-03-20","proceeding":"ICCV 2017 10","authors":["Miriam W. Huijser","Jan C. van Gemert"],"abstract":"This paper is on active learning where the goal is to reduce the data\nannotation burden by interacting with a (human) oracle during training.\nStandard active learning methods ask the oracle to annotate data samples.\nInstead, we take a profoundly different approach: we ask for annotations of the\ndecision boundary. We achieve this using a deep generative model to create\nnovel instances along a 1d line. A point on the decision boundary is revealed\nwhere the instances change class. Experimentally we show on three data sets\nthat our method can be plugged-in to other active learning schemes, that human\noracles can effectively annotate points on the decision boundary, that our\nmethod is robust to annotation noise, and that decision boundary annotations\nimprove over annotating data samples.","url_abs":"http://arxiv.org/abs/1703.06971v2","url_pdf":"http://arxiv.org/pdf/1703.06971v2.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":"active-decision-boundary-annotation-with-deep","repo_url":"https://github.com/MiriamHu/ActiveBoundary","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1703.06971","atlas_url":"https://app.syntology.ai/?focus=1703.06971","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}