{"id":"https://openalex.org/W7133341026","doi":"https://doi.org/10.48550/arxiv.2603.01498","title":"Tri-path DINO: Feature Complementary Learning for Remote Sensing Multi-Class Change Detection","display_name":"Tri-path DINO: Feature Complementary Learning for Remote Sensing Multi-Class Change Detection","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133341026","doi":"https://doi.org/10.48550/arxiv.2603.01498"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01498","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01498","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127941618","display_name":"Kai Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029378855","display_name":"Hangcheng Dong","orcid":"https://orcid.org/0000-0002-4880-6762"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Hang-Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121972929","display_name":"Zhenkai Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Shoulei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069395320","display_name":"Fupeng Wei","orcid":"https://orcid.org/0000-0002-2337-1483"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zhenkai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127877903","display_name":"Wei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Fupeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ding, Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhang, Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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":0.9940999746322632,"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":0.9940999746322632,"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":0.0012000000569969416,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.000699999975040555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5335999727249146},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5085999965667725},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.503000020980835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4903999865055084},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.48570001125335693},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47859999537467957},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4675999879837036},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.40849998593330383}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5705000162124634},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5335999727249146},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.503000020980835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.48570001125335693},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.38999998569488525},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3702000081539154},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.31200000643730164},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30559998750686646},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.29679998755455017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2867000102996826},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2736999988555908},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2624000012874603}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01498","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01498","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"remote":[1],"sensing":[2],"imagery,":[3],"multi":[4,108],"class":[5],"change":[6,191],"detection":[7,192],"(MCD)":[8],"is":[9,112],"crucial":[10],"for":[11,189,197],"fine":[12,103,175],"grained":[13,80,104,171,176],"monitoring,":[14],"yet":[15],"it":[16],"has":[17],"long":[18],"been":[19],"constrained":[20],"by":[21],"complex":[22,60],"scene":[23],"variations":[24],"and":[25,124,152,164,174,186,199],"the":[26,36,51,66,72,95,100,116,139,144,153,162],"scarcity":[27],"of":[28,54,102],"detailed":[29],"annotations.":[30],"To":[31],"address":[32],"this,":[33],"we":[34,64],"propose":[35],"Tripath":[37],"DINO":[38],"architecture,":[39],"which":[40],"adopts":[41,86],"a":[42,87,107,184,195],"three":[43],"path":[44,84],"complementary":[45],"feature":[46,74],"learning":[47,101],"strategy":[48],"to":[49,59,77,98,114],"facilitate":[50],"rapid":[52,198],"adaptation":[53],"pre":[55,68],"trained":[56,69],"foundation":[57],"models":[58],"vertical":[61],"domains.":[62],"Specifically,":[63],"employ":[65],"DINOv3":[67],"model":[70],"as":[71],"backbone":[73],"extraction":[75],"network":[76],"learn":[78],"coarse":[79,170],"features.":[81,105],"An":[82],"auxiliary":[83,165],"also":[85],"siamese":[88,96],"structure,":[89],"progressively":[90],"aggregating":[91],"intermediate":[92],"features":[93],"from":[94],"encoder":[97],"enhance":[99,125],"Finally,":[106],"scale":[109],"attention":[110],"mechanism":[111],"introduced":[113],"augment":[115],"decoder":[117],"network,":[118],"where":[119],"parallel":[120],"convolutions":[121],"adaptively":[122],"capture":[123],"contextual":[126],"information":[127],"under":[128],"different":[129],"receptive":[130],"fields.":[131],"The":[132],"proposed":[133],"method":[134],"achieves":[135],"optimal":[136],"performance":[137],"on":[138,142,169],"MCD":[140],"task":[141],"both":[143],"Gaza":[145],"facility":[146],"damage":[147,201],"assessment":[148],"dataset":[149],"(Gaza":[150],"change)":[151],"classic":[154],"SECOND":[155],"dataset.":[156],"GradCAM":[157],"visualizations":[158],"further":[159],"confirm":[160],"that":[161],"main":[163],"paths":[166],"naturally":[167],"focus":[168],"semantic":[172],"changes":[173],"structural":[177],"details,":[178],"respectively.":[179],"This":[180],"synergistic":[181],"complementarity":[182],"provides":[183],"robust":[185],"interpretable":[187],"solution":[188],"advanced":[190],"tasks,":[193],"offering":[194],"basis":[196],"accurate":[200],"assessment.":[202]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}