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To address these difficulties, we propose a three-stage skeleton-boundary\u2013guided network (SBGNet) for the COD task. Specifically, we design a novel skeleton-boundary label to be complementary to the typical pixel-wise mask annotation, emphasizing the interior skeleton and the boundary of the camouflaged object. Furthermore, the proposed feature guidance module (FGM) leverages the skeleton-boundary feature to guide the model to focus on both the interior and the boundary of the camouflaged object. Besides, we design a bidirectional feature flow path with the information interaction module (IIM) to propagate and integrate the semantic and texture information. Finally, we propose the dual feature distillation module (DFDM) to progressively refine the segmentation results in a fine-grained manner. Comprehensive experiments demonstrate that our SBGNet outperforms 20 state-of-the-art methods on three benchmarks in both qualitative and quantitative comparisons.<\/jats:p>","DOI":"10.1145\/3711869","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T12:32:25Z","timestamp":1736425945000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Skeleton-Boundary\u2013Guided Network for Camouflaged Object Detection"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9874-9719","authenticated-orcid":false,"given":"Yuzhen","family":"Niu","sequence":"first","affiliation":[{"name":"Fuzhou University, Fuzhou, China and China and Engineering Research Center of BigData Intelligence, Ministry of Education, Fuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6965-5195","authenticated-orcid":false,"given":"Yeyuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7397-4661","authenticated-orcid":false,"given":"Yuezhou","family":"Li","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0661-7428","authenticated-orcid":false,"given":"Jiabang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7408-2684","authenticated-orcid":false,"given":"Yuzhong","family":"Chen","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,2,20]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.07.080"},{"key":"e_1_3_1_3_2","first-page":"145","volume-title":"Proceedings of the International Conference on Information Technology","author":"Bhajantri Nagappa U.","year":"2006","unstructured":"Nagappa U. 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