{"id":"https://openalex.org/W4403534117","doi":"https://doi.org/10.1109/tai.2024.3483199","title":"Unsupervised Domain Adaptation on Point Clouds via High-Order Geometric Structure Modeling","display_name":"Unsupervised Domain Adaptation on Point Clouds via High-Order Geometric Structure Modeling","publication_year":2024,"publication_date":"2024-10-18","ids":{"openalex":"https://openalex.org/W4403534117","doi":"https://doi.org/10.1109/tai.2024.3483199"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2024.3483199","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2024.3483199","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-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":null,"display_name":"Jiang-Xing Cheng","orcid":"https://orcid.org/0009-0004-6502-9792"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiang-Xing Cheng","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036978677","display_name":"Huibin Lin","orcid":"https://orcid.org/0000-0002-7774-7722"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huibin Lin","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085340418","display_name":"Chun-Yang Zhang","orcid":"https://orcid.org/0000-0001-6151-7028"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun-Yang Zhang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":0.3679,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57667691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"5","issue":"12","first_page":"6121","last_page":"6133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9882000088691711,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7008512020111084},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5727400183677673},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5666626691818237},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47957247495651245},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.42968714237213135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3331628739833832},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18370887637138367},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10767793655395508},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.05703243613243103},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.05626422166824341}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7008512020111084},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5727400183677673},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5666626691818237},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47957247495651245},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.42968714237213135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3331628739833832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18370887637138367},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10767793655395508},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05703243613243103},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.05626422166824341},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2024.3483199","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2024.3483199","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G3172255338","display_name":null,"funder_award_id":"62476059","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2114948626","https://openalex.org/W2594519801","https://openalex.org/W2947713925","https://openalex.org/W2972931660","https://openalex.org/W2982683655","https://openalex.org/W2991485494","https://openalex.org/W3036560856","https://openalex.org/W3039883906","https://openalex.org/W3094046420","https://openalex.org/W3118644257","https://openalex.org/W3128716822","https://openalex.org/W3134878008","https://openalex.org/W3159481202","https://openalex.org/W3168312701","https://openalex.org/W4205629240","https://openalex.org/W4293094743","https://openalex.org/W4293193384","https://openalex.org/W4293193827","https://openalex.org/W4312317653","https://openalex.org/W4312379726","https://openalex.org/W4312780402","https://openalex.org/W4313127740","https://openalex.org/W4319300091","https://openalex.org/W4394625677","https://openalex.org/W4401460431","https://openalex.org/W6637618735","https://openalex.org/W6687484953","https://openalex.org/W6747904511","https://openalex.org/W6763103765","https://openalex.org/W6763422710","https://openalex.org/W6767325187","https://openalex.org/W6774187218","https://openalex.org/W6776700526","https://openalex.org/W6790825598","https://openalex.org/W6799875521","https://openalex.org/W6810220108","https://openalex.org/W6847671982","https://openalex.org/W6849654428"],"related_works":["https://openalex.org/W4389574804","https://openalex.org/W3016928466","https://openalex.org/W2997567050","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W2980582925"],"abstract_inverted_index":{"Point":[0],"clouds":[1,55],"can":[2,184],"capture":[3,137],"the":[4,23,45,53,73,83,90,104,123,130,138,149,172,181,187],"precise":[5],"geometric":[6,27,63,110,127,143],"information":[7],"of":[8,17,22,47,51,112,129,141,145,153,177],"objects":[9],"and":[10,20,39,49,126,132,174],"scenes,":[11],"which":[12],"are":[13,70],"an":[14,96],"important":[15],"source":[16,131],"3-D":[18,26],"data":[19,28],"one":[21,78],"most":[24],"popular":[25],"structures":[29,111,144],"for":[30],"cognitions":[31],"in":[32,66,77,85],"many":[33],"real-world":[34],"applications":[35],"like":[36],"automatic":[37],"driving":[38],"remote":[40],"sensing.":[41],"However,":[42],"due":[43],"to":[44,72,81,107,121,136,162,166],"influence":[46],"sensors":[48],"varieties":[50],"objects,":[52],"point":[54,113,146],"obtained":[56],"by":[57,158],"different":[58],"devices":[59],"may":[60],"suffer":[61],"obvious":[62],"changes,":[64],"resulting":[65],"domain":[67,79,98,155,164],"gaps":[68],"that":[69,180],"prone":[71],"neural":[74],"networks":[75],"trained":[76],"failing":[80],"preserve":[82],"performance":[84],"other":[86],"domains.":[87],"To":[88],"alleviate":[89],"above":[91],"problem,":[92],"this":[93],"article":[94],"proposes":[95],"unsupervised":[97],"adaptation":[99],"framework,":[100],"named":[101],"HO-GSM,":[102],"as":[103],"first":[105],"attempt":[106],"model":[108],"high-order":[109,142],"clouds.":[114,147],"First,":[115],"we":[116],"construct":[117],"multiple":[118],"self-supervised":[119],"tasks":[120],"learn":[122],"invariant":[124],"semantic":[125],"features":[128],"target":[133,154],"domains,":[134],"especially":[135],"feature":[139,151],"invariance":[140],"Second,":[148],"discriminative":[150],"space":[152],"is":[156],"acquired":[157],"using":[159],"contrastive":[160],"learning":[161],"refine":[163],"alignment":[165],"specific":[167],"class":[168],"level.":[169],"Experiments":[170],"on":[171],"PointDA-10":[173],"GraspNetPC-10":[175],"collection":[176],"datasets":[178],"show":[179],"proposed":[182],"HO-GSM":[183],"significantly":[185],"outperform":[186],"state-of-the-art":[188],"counterparts.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
