{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T16:22:38Z","timestamp":1777738958351,"version":"3.51.4"},"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":[[2018,7]]},"abstract":"<jats:p>Recent advances in 3D capturing devices and 3D\n\nmodeling software have led to extensive and diverse\n\n3D datasets, which usually have different distributions.\n\nCross-domain 3D model retrieval is becoming\n\nan important but challenging task. However,\n\nexisting works mainly focus on 3D model\n\nretrieval in a closed dataset, which seriously constrain\n\ntheir implementation for real applications. To\n\naddress this problem, we propose a novel crossdomain\n\n3D model retrieval method by visual domain\n\nadaptation. This method can inherit the advantage\n\nof deep learning to learn multi-view visual\n\nfeatures in the data-driven manner for 3D\n\nmodel representation. Moreover, it can reduce\n\nthe domain divergence by exploiting both domainshared\n\nand domain-specific features of different domains.\n\nConsequently, it can augment the discrimination\n\nof visual descriptors for cross-domain similarity\n\nmeasure. Extensive experiments on two popular\n\ndatasets, under three designed cross-domain\n\nscenarios, demonstrate the superiority and effectiveness\n\nof the proposed method by comparing\n\nagainst the state-of-the-art methods. Especially, the\n\nproposed method can significantly outperform the\n\nmost recent method for cross-domain 3D model retrieval\n\nand the champion of Shrec\u201916 Large-Scale\n\n3D Shape Retrieval from ShapeNet Core55.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/115","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"828-834","source":"Crossref","is-referenced-by-count":17,"title":["Cross-Domain 3D Model Retrieval via Visual Domain Adaption"],"prefix":"10.24963","author":[{"given":"Anan","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shu","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhui","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weizhi","family":"Nie","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuting","family":"Su","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","theme":"Artificial Intelligence","location":"Stockholm, Sweden","acronym":"IJCAI-2018","number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2018,7,13]]},"end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:50:03Z","timestamp":1530755403000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/115"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/115","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}