{"id":"https://openalex.org/W7133354221","doi":"https://doi.org/10.48550/arxiv.2603.01332","title":"Perspective-Equivariant Fine-tuning for Multispectral Demosaicing without Ground Truth","display_name":"Perspective-Equivariant Fine-tuning for Multispectral Demosaicing without Ground Truth","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133354221","doi":"https://doi.org/10.48550/arxiv.2603.01332"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01332","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01332","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01332","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127908646","display_name":"Andrew Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Andrew","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127919581","display_name":"Mike Davies","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Davies, Mike","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5127908646"],"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.3093000054359436,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.3093000054359436,"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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.10559999942779541,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.1046999990940094,"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/multispectral-image","display_name":"Multispectral image","score":0.8090999722480774},{"id":"https://openalex.org/keywords/demosaicing","display_name":"Demosaicing","score":0.6520000100135803},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5627999901771545},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.476500004529953},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.40639999508857727},{"id":"https://openalex.org/keywords/color-filter-array","display_name":"Color filter array","score":0.3179999887943268}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.8090999722480774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7390999794006348},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6646000146865845},{"id":"https://openalex.org/C27624317","wikidata":"https://www.wikidata.org/wiki/Q263499","display_name":"Demosaicing","level":5,"score":0.6520000100135803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6502000093460083},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5627999901771545},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.40639999508857727},{"id":"https://openalex.org/C177299597","wikidata":"https://www.wikidata.org/wiki/Q2468214","display_name":"Color filter array","level":5,"score":0.3179999887943268},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.25999999046325684},{"id":"https://openalex.org/C5622133","wikidata":"https://www.wikidata.org/wiki/Q812133","display_name":"Bayer filter","level":5,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01332","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01332","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01332","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01332","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":"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":{"Multispectral":[0],"demosaicing":[1,50,73],"is":[2],"crucial":[3],"to":[4,18,65,75],"reconstruct":[5],"full-resolution":[6],"spectral":[7,111],"images":[8],"from":[9,16,34,51],"snapshot":[10],"mosaiced":[11,52],"measurements,":[12],"enabling":[13],"real-time":[14],"imaging":[15,63],"neurosurgery":[17],"autonomous":[19],"driving.":[20],"Classical":[21],"methods":[22,74],"are":[23],"blurry,":[24],"while":[25],"supervised":[26,118],"learning":[27],"requires":[28],"costly":[29],"ground":[30],"truth":[31],"(GT)":[32],"obtained":[33],"slow":[35],"line-scanning":[36],"systems.":[37],"We":[38],"propose":[39],"Perspective-Equivariant":[40],"Fine-tuning":[41],"for":[42,92],"Demosaicing":[43],"(PEFD),":[44],"a":[45,67],"framework":[46],"that":[47],"learns":[48,82],"multispectral":[49],"measurements":[53],"alone.":[54],"PEFD":[55,101],"a)":[56],"exploits":[57],"the":[58],"projective":[59],"geometry":[60],"of":[61],"camera-based":[62],"systems":[64],"leverage":[66],"richer":[68],"group":[69],"structure":[70],"than":[71],"previous":[72],"recover":[76],"more":[77],"null-space":[78],"information,":[79],"and":[80,98,109],"b)":[81],"efficiently":[83],"without":[84],"GT":[85],"by":[86],"adapting":[87],"pretrained":[88],"foundation":[89],"models":[90],"designed":[91],"1-3":[93],"channel":[94],"imaging.":[95],"On":[96],"intraoperative":[97],"automotive":[99],"datasets,":[100],"recovers":[102],"fine":[103],"details":[104],"such":[105],"as":[106],"blood":[107],"vessels":[108],"preserves":[110],"fidelity,":[112],"substantially":[113],"outperforming":[114],"recent":[115],"approaches,":[116],"nearing":[117],"performance.":[119]},"counts_by_year":[],"updated_date":"2026-03-04T07:09:34.246503","created_date":"2026-03-04T00:00:00"}
