{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:36:17Z","timestamp":1779381377693,"version":"3.53.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Camouflaged Object Detection (COD) aims to segment objects that blend in with their surroundings. Most existing methods mainly tackle this issue by a single-stage framework, which tends to degrade performance in the face of small objects, low-contrast objects and objects with diverse appearances. In this paper, we propose a novel Progressive Enhancement Network (PENet) for COD by imitating the human visual detection system, which follows a three-stage detection process: locate objects, refine textures and restore boundary. Specifically, our PENet contains three key modules, i.e., the object location module (OLM), the group attention module (GAM) and the context feature restoration module (CFRM). The OLM is designed to position the object globally, the GAM is developed to refine both high-level semantic and low-level texture feature representation, and the CFRM is leveraged to effectively aggregate multi-level features for progressively restoring the clear boundary. Extensive results demonstrate that our PENet significantly outperforms 32 state-of-the-art methods on four widely used benchmark datasets<\/jats:p>","DOI":"10.24963\/ijcai.2023\/124","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"1116-1124","source":"Crossref","is-referenced-by-count":30,"title":["Locate, Refine and Restore: A Progressive Enhancement Network for Camouflaged Object Detection"],"prefix":"10.24963","author":[{"given":"Xiaofei","family":"Li","sequence":"first","affiliation":[{"name":"Laboratory for Big Data and Decision, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Yang","sequence":"additional","affiliation":[{"name":"Laboratory for Big Data and Decision, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuohao","family":"Li","sequence":"additional","affiliation":[{"name":"Laboratory for Big Data and Decision, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Lei","sequence":"additional","affiliation":[{"name":"Laboratory for Big Data and Decision, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Laboratory for Big Data and Decision, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Chen","sequence":"additional","affiliation":[{"name":"Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:36:35Z","timestamp":1691742995000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/124"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/124","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}