{"type":"ScholarlyArticle","title":"Contour-based Interactive Segmentation","authors":[{"name":"Polina Popenova","slug":"polina-popenova","given":"Polina","family":"Popenova","affiliation":"Samsung Research"},{"name":"Danil Galeev","slug":"danil-galeev","given":"Danil","family":"Galeev","affiliation":"Samsung Research"},{"name":"Anna Vorontsova","slug":"anna-vorontsova","given":"Anna","family":"Vorontsova","affiliation":"Samsung Research"},{"name":"Anton Konushin","slug":"anton-konushin","given":"Anton","family":"Konushin","affiliation":"Samsung Research"}],"abstract":"Recent advances in interactive segmentation (IS)\r\nallow speeding up and simplifying image editing\r\nand labeling greatly. The majority of modern IS\r\napproaches accept user input in the form of clicks.\r\nHowever, using clicks may require too many user\r\ninteractions, especially when selecting small ob-\r\njects, minor parts of an object, or a group of ob-\r\njects of the same type. In this paper, we consider\r\nsuch a natural form of user interaction as a loose\r\ncontour, and introduce a contour-based IS method.\r\nWe evaluate the proposed method on the standard\r\nsegmentation benchmarks, our novel UserContours\r\ndataset, and its subset UserContours-G containing\r\ndifficult segmentation cases. Through experiments,\r\nwe demonstrate that a single contour provides the\r\nsame accuracy as multiple clicks, thus reducing the\r\nrequired amount of user interactions.","doi":"10.24963/ijcai.2023/147","url":"https://ijcai.org/proceedings/2023/147","pdf":"https://ijcai.org/proceedings/2023/0147.pdf","markdown":"https://ijcai.org/proceedings/2023/147.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/147","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Computer Vision","track":"Main Track","number":147,"pages":{"first":1322,"last":1330},"keywords":["Computer Vision: CV: Segmentation","Computer Vision: CV: Machine learning for vision"],"videos":[],"references":[{"position":1,"raw":"[Acuna et al., 2018] David Acuna, Huan Ling, Amlan Kar, and Sanja Fidler. 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