{"id":"https://openalex.org/W4417281780","doi":"https://doi.org/10.1109/iccv51701.2025.00102","title":"Deep Incomplete Multi-View Clustering with Distribution Dual-Consistency Recovery Guidance","display_name":"Deep Incomplete Multi-View Clustering with Distribution Dual-Consistency Recovery Guidance","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4417281780","doi":"https://doi.org/10.1109/iccv51701.2025.00102"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.00102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.11017","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101875008","display_name":"Jiaqi Jin","orcid":"https://orcid.org/0009-0000-0510-4472"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Jin","raw_affiliation_strings":["National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100656645","display_name":"Siwei Wang","orcid":"https://orcid.org/0000-0001-9517-262X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siwei Wang","raw_affiliation_strings":["Academy of Military Sciences,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009251223","display_name":"Zhibin Dong","orcid":"https://orcid.org/0000-0001-7829-4924"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Dong","raw_affiliation_strings":["National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103088081","display_name":"Xihong Yang","orcid":"https://orcid.org/0000-0002-3260-869X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xihong Yang","raw_affiliation_strings":["National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727888","display_name":"Xinwang Liu","orcid":"https://orcid.org/0000-0001-9066-1475"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwang Liu","raw_affiliation_strings":["National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069681054","display_name":"En Zhu","orcid":"https://orcid.org/0000-0003-2305-7555"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"En Zhu","raw_affiliation_strings":["National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027802880","display_name":"Kunlun He","orcid":"https://orcid.org/0000-0002-3335-5700"},"institutions":[{"id":"https://openalex.org/I2802939634","display_name":"Chinese PLA General Hospital","ror":"https://ror.org/04gw3ra78","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2802939634"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunlun He","raw_affiliation_strings":["Chinese PLA General hospital,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese PLA General hospital,Beijing,China","institution_ids":["https://openalex.org/I2802939634"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1016","last_page":"1026"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.3668999969959259,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.3668999969959259,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.1753000020980835,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.14329999685287476,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8152999877929688},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5771999955177307},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.552299976348877},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49079999327659607},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4668999910354614},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4235999882221222},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.3091000020503998}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8152999877929688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6269999742507935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6104999780654907},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5771999955177307},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.552299976348877},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49079999327659607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47920000553131104},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4668999910354614},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3885999917984009},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.28760001063346863},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.00102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.11017","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.11017","pdf_url":"https://arxiv.org/pdf/2503.11017","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2503.11017","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.11017","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.11017","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.11017","pdf_url":"https://arxiv.org/pdf/2503.11017","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8786042905","display_name":null,"funder_award_id":"62276271,62406329,62476281","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-view":[0],"clustering":[1,74,89],"leverages":[2],"complementary":[3],"representations":[4],"from":[5,68],"diverse":[6],"sources":[7],"to":[8,19,35,50,108],"enhance":[9],"performance.":[10],"However,":[11],"real-world":[12],"data":[13],"often":[14],"suffer":[15],"incomplete":[16,87,158],"cases":[17],"due":[18],"factors":[20],"like":[21],"privacy":[22],"concerns":[23],"and":[24,56,72,103,140],"device":[25],"malfunctions.":[26],"A":[27],"key":[28],"challenge":[29],"is":[30],"effectively":[31],"utilizing":[32],"available":[33],"instances":[34],"recover":[36],"missing":[37,114],"views.":[38,115],"Existing":[39],"methods":[40],"frequently":[41],"overlook":[42],"the":[43,110,119,152,157],"heterogeneity":[44],"among":[45],"views":[46],"during":[47],"recovery,":[48],"leading":[49],"significant":[51],"distribution":[52,106,111],"discrepancies":[53],"between":[54],"recovered":[55],"true":[57],"data.":[58],"Additionally,":[59],"many":[60],"approaches":[61],"focus":[62],"on":[63,149],"cross-view":[64,73,105,141],"correlations,":[65],"neglecting":[66],"insights":[67],"intra-view":[69,134],"reliable":[70,122],"structure":[71],"structure.":[75],"To":[76,116],"address":[77],"these":[78],"issues,":[79],"we":[80,125],"propose":[81],"BURG,":[82],"a":[83,100,127],"novel":[84],"method":[85],"for":[86,118],"multi-view":[88,159],"with":[90],"distriBution":[91],"dUal-consistency":[92],"Recovery":[93],"Guidance.":[94],"We":[95],"treat":[96],"each":[97],"sample":[98],"as":[99],"distinct":[101],"category":[102,123],"perform":[104],"transfer":[107],"predict":[109],"space":[112],"of":[113,121,154],"compensate":[117],"lack":[120],"information,":[124],"design":[126],"dual-consistency":[128],"guided":[129,136,143],"recovery":[130],"strategy":[131],"that":[132],"includes":[133],"alignment":[135,142],"by":[137,144],"neighbor-aware":[138],"consistency":[139],"prototypical":[145],"consistency.":[146],"Extensive":[147],"experiments":[148],"benchmarks":[150],"demonstrate":[151],"superiority":[153],"BURG":[155],"in":[156],"scenario.":[160]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}