{"id":"https://openalex.org/W4401417233","doi":"https://doi.org/10.1109/icra57147.2024.10611402","title":"Masked Local-Global Representation Learning for 3D Point Cloud Domain Adaptation","display_name":"Masked Local-Global Representation Learning for 3D Point Cloud Domain Adaptation","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401417233","doi":"https://doi.org/10.1109/icra57147.2024.10611402"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611402","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10611402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","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/A5028438544","display_name":"Bowei Xing","orcid":"https://orcid.org/0009-0001-3254-3902"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bowei Xing","raw_affiliation_strings":["Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015981200","display_name":"Xianghua Ying","orcid":"https://orcid.org/0000-0002-9785-0727"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghua Ying","raw_affiliation_strings":["Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101686254","display_name":"Ruibin Wang","orcid":"https://orcid.org/0000-0003-0968-6152"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruibin Wang","raw_affiliation_strings":["Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology,Beijing,China,100871","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028438544"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.352,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5425966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"30","issue":null,"first_page":"418","last_page":"424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9916999936103821,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9810000061988831,"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/point-cloud","display_name":"Point cloud","score":0.7509717345237732},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7486341595649719},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6897767782211304},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6333320736885071},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5859065651893616},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5004348754882812},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4721396267414093},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4635125398635864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35502660274505615},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08970808982849121}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7509717345237732},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7486341595649719},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6897767782211304},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6333320736885071},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5859065651893616},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5004348754882812},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4721396267414093},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4635125398635864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35502660274505615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08970808982849121},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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:10.1109/icra57147.2024.10611402","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10611402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":40,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1920022804","https://openalex.org/W1988197306","https://openalex.org/W2125865219","https://openalex.org/W2584886900","https://openalex.org/W2593768305","https://openalex.org/W2594519801","https://openalex.org/W2962687275","https://openalex.org/W2963107255","https://openalex.org/W2979750740","https://openalex.org/W3034459762","https://openalex.org/W3036560856","https://openalex.org/W3111535274","https://openalex.org/W3116959466","https://openalex.org/W3118644257","https://openalex.org/W3153465022","https://openalex.org/W3175294391","https://openalex.org/W3175370657","https://openalex.org/W3202611145","https://openalex.org/W4226254397","https://openalex.org/W4242710771","https://openalex.org/W4293363567","https://openalex.org/W4312312750","https://openalex.org/W4312379726","https://openalex.org/W4312497372","https://openalex.org/W4312592225","https://openalex.org/W4312788538","https://openalex.org/W4312793137","https://openalex.org/W4313127740","https://openalex.org/W4313156423","https://openalex.org/W4319300091","https://openalex.org/W4367146896","https://openalex.org/W4394671432","https://openalex.org/W6637618735","https://openalex.org/W6687484953","https://openalex.org/W6739778489","https://openalex.org/W6746262046","https://openalex.org/W6763103765","https://openalex.org/W6763422710","https://openalex.org/W6767325187"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W3156096827"],"abstract_inverted_index":{"Point":[0],"cloud":[1,24,58,94,150,177],"is":[2],"a":[3,52,67],"popular":[4],"and":[5,37,77,86,103,145,153,165],"widely":[6],"used":[7],"geometric":[8,20],"representation,":[9],"which":[10,33,131],"has":[11],"attracted":[12],"significant":[13],"attention":[14],"in":[15,41,44,66,118,137],"3D":[16,148],"vision.":[17],"However,":[18],"the":[19,119,123,133,160,171],"variability":[21],"of":[22,162],"point":[23,57,93,149,176],"representations":[25],"across":[26,96],"different":[27],"datasets":[28],"can":[29,127,169],"cause":[30],"domain":[31,59,178],"discrepancies,":[32],"hinder":[34],"knowledge":[35,105],"transfer":[36,104],"model":[38],"generalization,":[39],"resulting":[40],"degraded":[42],"performance":[43,174],"target":[45,138],"domain.":[46,139],"In":[47],"this":[48],"paper,":[49],"we":[50,110,168],"present":[51],"novel":[53],"approach":[54],"to":[55,81,99,108],"improve":[56],"adaptation":[60],"by":[61],"employing":[62],"masked":[63,74,78],"representation":[64,95,102],"learning":[65,91,136],"self-supervised":[68],"manner.":[69],"Specifically,":[70],"our":[71,163],"method":[72,164],"combines":[73],"feature":[75,121],"prediction":[76],"sample":[79],"consistency":[80],"encode":[82],"both":[83],"local":[84],"structure":[85],"global":[87],"semantic":[88,154],"information":[89],"for":[90,147],"invariant":[92],"domains.":[97],"Moreover,":[98],"learn":[100],"domain-specific":[101],"from":[106],"source":[107],"target,":[109],"propose":[111],"prototype-calibrated":[112],"self-training.":[113],"By":[114],"exploiting":[115],"class-wise":[116],"prototypes":[117],"shared":[120],"space,":[122],"soft":[124],"pseudo":[125],"labels":[126],"be":[128],"adaptively":[129],"denoised,":[130],"benefits":[132],"decision":[134],"boundary":[135],"We":[140],"conduct":[141],"experiments":[142],"on":[143,175],"PointDA-10":[144],"PointSegDA":[146],"shape":[151],"classification":[152],"segmentation,":[155],"respectively.":[156],"The":[157],"results":[158],"demonstrate":[159],"effectiveness":[161],"show":[166],"that":[167],"achieve":[170],"new":[172],"state-of-the-art":[173],"adaptation.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
