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Existing object detection models, typically trained on natural scenes, tend to perform poorly in this domain. To address this limitation, we summarize the principles of composition in Thangka and identify key spatial and co\u2010occurrence priors specific to ritual implements. Based on these insights, we propose GPCDet: a guided by principles of composition detector that integrates domain\u2010specific priors into the detection process. Specifically, we introduce a spatial coordinate attention module to emphasize critical spatial regions where implements frequently appear. In addition, we design a graph convolution network\u2010auxiliary detection module to model inter\u2010category co\u2010occurrence, thereby enhancing feature representation and improving classification performance. Experiments on the newly curated ritual implements in Thangka (RITK) dataset show that GPCDet achieves substantial improvements over existing methods, establishing a new state\u2010of\u2010the\u2010art baseline for this challenging\u00a0task.<\/jats:p>","DOI":"10.1049\/ipr2.70271","type":"journal-article","created":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T03:05:26Z","timestamp":1767755126000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Guided by Principles of Composition: A Domain\u2010Specific Priors Based Detector for Recognizing Ritual Implements in Thangka"],"prefix":"10.1049","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0602-9360","authenticated-orcid":false,"given":"Jiachen","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China"},{"name":"Engineering Research Center of Intelligent Service Technology for Digital Publishing Ministry of Education Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolong","family":"Peng","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Intelligent Service Technology for Digital Publishing Ministry of Education Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinyu","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China"},{"name":"Engineering Research Center of Intelligent Service Technology for Digital Publishing Ministry of Education Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanchun","family":"Ma","sequence":"additional","affiliation":[{"name":"Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts Wuhan Vocational College of Software and Engineering Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbo","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengzi","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China"},{"name":"Engineering Research Center of Intelligent Service Technology for Digital Publishing Ministry of Education Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"265","published-online":{"date-parts":[[2026,1,6]]},"reference":[{"issue":"2","key":"e_1_2_13_2_1","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1049\/ipr2.12953","article-title":"Category\u2010Related Attention Domain Adaptation for One\u2010Stage Cross\u2010Domain Object Detection","volume":"18","author":"Guan S.","year":"2024","journal-title":"IET Image Processing"},{"issue":"3","key":"e_1_2_13_3_1","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1049\/ipr2.12972","article-title":"CSFFNet: Lightweight Cross\u2010Scale Feature Fusion Network for Salient Object Detection in Remote Sensing Images","volume":"18","author":"Wang L.","year":"2024","journal-title":"IET Image Processing"},{"key":"e_1_2_13_4_1","doi-asserted-by":"crossref","unstructured":"S.Zhang C.Chi Y.Yao Z.Lei andS. 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