{"id":"https://openalex.org/W4387848902","doi":"https://doi.org/10.1145/3583780.3614982","title":"MultiCAD: Contrastive Representation Learning for Multi-modal 3D Computer-Aided Design Models","display_name":"MultiCAD: Contrastive Representation Learning for Multi-modal 3D Computer-Aided Design Models","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387848902","doi":"https://doi.org/10.1145/3583780.3614982"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3614982","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3614982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054455904","display_name":"Weijian Ma","orcid":"https://orcid.org/0009-0004-0650-6448"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijian Ma","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-0650-6448","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033254880","display_name":"Minyang Xu","orcid":"https://orcid.org/0000-0002-1594-2776"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minyang Xu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1594-2776","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002521830","display_name":"Xueyang Li","orcid":"https://orcid.org/0009-0004-7833-0170"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyang Li","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-7833-0170","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046420009","display_name":"Xiangdong Zhou","orcid":"https://orcid.org/0000-0002-5538-7367"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Zhou","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5538-7367","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":6.6331,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.96740817,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1766","last_page":"1776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7069801092147827},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.5910625457763672},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5817939043045044},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5635653734207153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5473501682281494},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5391455292701721},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5222806930541992},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.48136478662490845},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.43304723501205444},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4312751889228821},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40429314970970154},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3876160979270935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7069801092147827},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.5910625457763672},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5817939043045044},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5635653734207153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5473501682281494},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5391455292701721},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5222806930541992},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.48136478662490845},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.43304723501205444},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4312751889228821},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40429314970970154},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3876160979270935},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3614982","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3614982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.41999998688697815,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1352607027","display_name":null,"funder_award_id":"2018YFB1402600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2485315997","https://openalex.org/W2963158438","https://openalex.org/W2963351448","https://openalex.org/W2964137676","https://openalex.org/W2972931660","https://openalex.org/W3026092005","https://openalex.org/W3034459762","https://openalex.org/W3034572187","https://openalex.org/W3035057392","https://openalex.org/W3106655268","https://openalex.org/W3133696297","https://openalex.org/W3133849783","https://openalex.org/W3159309302","https://openalex.org/W3162843412","https://openalex.org/W3167804518","https://openalex.org/W3170409640","https://openalex.org/W3176403475","https://openalex.org/W3180125285","https://openalex.org/W3184000328","https://openalex.org/W3185376398","https://openalex.org/W3201927751","https://openalex.org/W3211034991","https://openalex.org/W3217122878","https://openalex.org/W4214718285","https://openalex.org/W4234552385","https://openalex.org/W4281931222","https://openalex.org/W4308600730","https://openalex.org/W4312246270","https://openalex.org/W4312317653","https://openalex.org/W4312460555","https://openalex.org/W4312559613","https://openalex.org/W4313034350","https://openalex.org/W6600234944","https://openalex.org/W6777179611","https://openalex.org/W6790690058","https://openalex.org/W6794944964","https://openalex.org/W6795893160","https://openalex.org/W7075367004"],"related_works":["https://openalex.org/W4389505417","https://openalex.org/W4301143707","https://openalex.org/W2952745240","https://openalex.org/W2962931510","https://openalex.org/W4380551887","https://openalex.org/W4285159263","https://openalex.org/W2904518532","https://openalex.org/W4280529741","https://openalex.org/W4293919860","https://openalex.org/W2963650472"],"abstract_inverted_index":{"CAD":[0,115],"models":[1],"are":[2,15,80],"multimodal":[3,50,68,112,126],"data":[4],"where":[5,54],"information":[6,43],"and":[7,13,20,77,97,114,134],"knowledge":[8],"contained":[9],"in":[10,34],"construction":[11,101],"sequences":[12],"shapes":[14],"complementary":[16],"to":[17,88,107],"each":[18],"other":[19],"representation":[21,91,127],"learning":[22,37,52,62,128],"methods":[23,36,136],"should":[24],"consider":[25],"both":[26,45,75],"of":[27,124],"them.":[28],"Such":[29],"traits":[30],"have":[31],"been":[32],"neglected":[33],"previous":[35],"unimodal":[38,135],"representations.":[39],"To":[40],"leverage":[41],"the":[42,90,122,132],"from":[44,56],"modalities,":[46],"we":[47],"develop":[48],"a":[49,66,84],"contrastive":[51,61,69],"strategy":[53,87],"features":[55],"different":[57],"modalities":[58],"interact":[59],"via":[60],"paradigm,":[63],"driven":[64],"by":[65],"novel":[67],"loss.":[70],"Two":[71],"pretext":[72],"tasks":[73,109],"on":[74,93],"geometry":[76],"sequence":[78,116],"domains":[79],"designed":[81],"along":[82],"with":[83],"two-stage":[85],"training":[86],"make":[89],"focus":[92],"encoding":[94],"geometric":[95],"details":[96],"decoding":[98],"representations":[99],"into":[100],"sequences,":[102],"thus":[103],"being":[104],"more":[105],"applicable":[106],"downstream":[108],"such":[110],"as":[111],"retrieval":[113],"reconstruction.":[117],"Experimental":[118],"results":[119],"show":[120],"that":[121],"performance":[123],"our":[125],"scheme":[129],"has":[130],"surpassed":[131],"baselines":[133],"significantly.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}