{"id":"https://openalex.org/W7083680583","doi":"https://doi.org/10.48550/arxiv.2509.22450","title":"SSVIF: Self-Supervised Segmentation-Oriented Visible and Infrared Image Fusion","display_name":"SSVIF: Self-Supervised Segmentation-Oriented Visible and Infrared Image Fusion","publication_year":2025,"publication_date":"2025-09-26","ids":{"openalex":"https://openalex.org/W7083680583","doi":"https://doi.org/10.48550/arxiv.2509.22450"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2509.22450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22450","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2509.22450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhao, Zixian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zixian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhang, Xingchen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xingchen","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":true,"primary_topic":{"id":"https://openalex.org/T11688","display_name":"Microbial infections and disease research","score":0.08839999884366989,"subfield":{"id":"https://openalex.org/subfields/2404","display_name":"Microbiology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11688","display_name":"Microbial infections and disease research","score":0.08839999884366989,"subfield":{"id":"https://openalex.org/subfields/2404","display_name":"Microbiology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10497","display_name":"Fungal and yeast genetics research","score":0.07940000295639038,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.07620000094175339,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7675999999046326},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6389999985694885},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5248000025749207},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5026999711990356},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4853000044822693},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4311999976634979},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4269999861717224},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4113999903202057}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7675999999046326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290999889373779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7275000214576721},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6389999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5680000185966492},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5026999711990356},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4853000044822693},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4269999861717224},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4113999903202057},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31290000677108765},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.27160000801086426},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.265500009059906}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2509.22450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22450","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2509.22450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22450","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6927179098129272}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Visible":[0],"and":[1,24,37,97,121,154,195],"infrared":[2],"image":[3,187],"fusion":[4,134],"(VIF)":[5],"has":[6],"gained":[7],"significant":[8],"attention":[9],"in":[10,18],"recent":[11],"years":[12],"due":[13],"to":[14,75,136],"its":[15],"wide":[16],"application":[17],"tasks":[19,62,86],"such":[20],"as":[21],"scene":[22],"segmentation":[23,89,120,145],"object":[25,91],"detection.":[26],"VIF":[27,35,39,54,79,111,193],"methods":[28,36,42,55,80,112,194],"can":[29],"be":[30,203],"broadly":[31],"classified":[32],"into":[33],"traditional":[34,76,192],"application-oriented":[38,53,78],"methods.":[40],"Traditional":[41],"focus":[43],"solely":[44],"on":[45,63,170,184],"improving":[46],"the":[47,58,115,133,142,174],"quality":[48],"of":[49,60,144,176],"fused":[50,64],"images,":[51],"while":[52],"additionally":[56],"consider":[57],"performance":[59],"downstream":[61,85],"images":[65],"by":[66],"introducing":[67],"task-specific":[68],"loss":[69],"terms":[70],"during":[71],"training.":[72],"However,":[73],"compared":[74],"methods,":[77],"require":[81],"datasets":[82,172],"labeled":[83],"for":[84,109,160],"(e.g.,":[87],"semantic":[88,139],"or":[90],"detection),":[92],"making":[93],"data":[94],"acquisition":[95],"labor-intensive":[96],"time-consuming.":[98],"To":[99],"address":[100],"this":[101],"issue,":[102],"we":[103,125,148],"propose":[104],"a":[105,127,150,155],"self-supervised":[106,129,166],"training":[107,152],"framework":[108],"segmentation-oriented":[110,198],"(SSVIF).":[113],"Leveraging":[114],"consistency":[116],"between":[117],"feature-level":[118],"fusion-based":[119,123],"pixel-level":[122],"segmentation,":[124],"introduce":[126],"novel":[128],"task-cross-segmentation":[130],"consistency-that":[131],"enables":[132],"model":[135],"learn":[137],"high-level":[138],"features":[140],"without":[141],"supervision":[143],"labels.":[146],"Additionally,":[147],"design":[149],"two-stage":[151],"strategy":[153],"dynamic":[156],"weight":[157],"adjustment":[158],"method":[159],"effective":[161],"joint":[162],"learning":[163],"within":[164],"our":[165,177,189],"framework.":[167],"Extensive":[168],"experiments":[169],"public":[171],"demonstrate":[173],"effectiveness":[175],"proposed":[178],"SSVIF.":[179],"Remarkably,":[180],"although":[181],"trained":[182],"only":[183],"unlabeled":[185],"visible-infrared":[186],"pairs,":[188],"SSVIF":[190],"outperforms":[191],"rivals":[196],"supervised":[197],"ones.":[199],"Our":[200],"code":[201],"will":[202],"released":[204],"upon":[205],"acceptance.":[206]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}