{"id":"https://openalex.org/W7148665282","doi":"https://doi.org/10.48550/arxiv.2604.02160","title":"CoRegOVCD: Consistency-Regularized Open-Vocabulary Change Detection","display_name":"CoRegOVCD: Consistency-Regularized Open-Vocabulary Change Detection","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148665282","doi":"https://doi.org/10.48550/arxiv.2604.02160"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02160","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02160","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.02160","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070010578","display_name":"Wei Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Weidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004252370","display_name":"Hanbin Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Hanbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132862149","display_name":"Zihan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132884608","display_name":"Yikai Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yikai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132909375","display_name":"Feifan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Feifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.006500000134110451,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.005799999926239252,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.8126000165939331},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5995000004768372},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5397999882698059},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5358999967575073},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5073000192642212},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.46059998869895935},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.43540000915527344},{"id":"https://openalex.org/keywords/spatial-change","display_name":"Spatial change","score":0.42570000886917114}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.8126000165939331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380000114440918},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5995000004768372},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5358999967575073},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5073000192642212},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C2993836695","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial change","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40709999203681946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3986999988555908},{"id":"https://openalex.org/C2985909886","wikidata":"https://www.wikidata.org/wiki/Q193147","display_name":"Spatial coherence","level":3,"score":0.39559999108314514},{"id":"https://openalex.org/C2989469682","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Change analysis","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C36391188","wikidata":"https://www.wikidata.org/wiki/Q1939117","display_name":"Semantic change","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.29030001163482666},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28110000491142273},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02160","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02160","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":"doi:10.48550/arxiv.2604.02160","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02160","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"change":[2,11,32,39,81,98,128],"detection":[3,33],"(CD)":[4],"aims":[5],"to":[6,56,179],"identify":[7],"where":[8],"land-cover":[9,72],"semantics":[10],"across":[12,59],"time,":[13],"but":[14],"most":[15],"existing":[16],"methods":[17],"still":[18],"assume":[19],"a":[20,42,90,185],"fixed":[21],"label":[22],"space":[23],"and":[24,66,78,107,121,140,149,157,165,183],"therefore":[25],"cannot":[26],"answer":[27],"arbitrary":[28],"user-defined":[29],"queries.":[30],"Open-vocabulary":[31],"(OVCD)":[34],"instead":[35],"asks":[36],"for":[37],"the":[38,46,67,108,172],"mask":[40],"of":[41,70,188],"queried":[43],"concept.":[44],"In":[45],"fully":[47],"training-free":[48,91,175],"setting,":[49],"however,":[50],"dense":[51,92],"concept":[52,115],"responses":[53,116,148],"are":[54],"difficult":[55],"compare":[57],"directly":[58],"dates:":[60],"appearance":[61],"variation,":[62],"weak":[63],"cross-concept":[64],"competition,":[65],"spatial":[68,151],"continuity":[69],"many":[71],"categories":[73],"often":[74],"produce":[75],"noisy,":[76],"fragmented,":[77],"semantically":[79],"unreliable":[80],"evidence.":[82],"We":[83],"propose":[84],"Consistency-Regularized":[85],"Open-Vocabulary":[86],"Change":[87],"Detection":[88],"(CoRegOVCD),":[89],"inference":[93],"framework":[94],"that":[95],"reformulates":[96],"concept-specific":[97],"as":[99],"calibrated":[100],"posterior":[101],"discrepancy.":[102],"Competitive":[103],"Posterior":[104,110],"Calibration":[105],"(CPC)":[106],"Semantic":[109],"Delta":[111],"(SPD)":[112],"convert":[113],"raw":[114],"into":[117],"competition-aware":[118],"queried-concept":[119],"posteriors":[120],"quantify":[122],"their":[123],"cross-temporal":[124],"discrepancy,":[125],"making":[126],"semantic":[127],"evidence":[129],"more":[130],"comparable":[131],"without":[132],"explicit":[133],"instance":[134],"matching.":[135],"Geometry-Token":[136],"Consistency":[137],"Gate":[138],"(GeoGate)":[139],"Regional":[141],"Consensus":[142],"Discrepancy":[143],"(RCD)":[144],"further":[145],"suppress":[146],"unsupported":[147],"improve":[150],"coherence":[152],"through":[153],"geometry-aware":[154],"structural":[155],"verification":[156],"regional":[158],"consensus.":[159],"Across":[160],"four":[161],"benchmarks":[162],"spanning":[163],"building-oriented":[164],"multi-class":[166],"settings,":[167],"CoRegOVCD":[168],"consistently":[169],"improves":[170],"over":[171],"strongest":[173],"previous":[174],"baseline":[176],"by":[177],"2.24":[178],"4.98":[180],"F1$_C$":[181,190],"points":[182],"reaches":[184],"six-class":[186],"average":[187],"47.50%":[189],"on":[191],"SECOND.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-04T00:00:00"}
