{"id":"https://openalex.org/W4390100355","doi":"https://doi.org/10.1145/3589132.3625570","title":"Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation","display_name":"Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4390100355","doi":"https://doi.org/10.1145/3589132.3625570"},"language":"en","primary_location":{"id":"doi:10.1145/3589132.3625570","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625570","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625570","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625570","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063375262","display_name":"Linhan Wang","orcid":"https://orcid.org/0009-0000-8057-1767"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linhan Wang","raw_affiliation_strings":["Computer Science, Virginia Tech, Falls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0009-0000-8057-1767","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Falls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034757629","display_name":"Shuo Lei","orcid":"https://orcid.org/0000-0001-7031-2438"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuo Lei","raw_affiliation_strings":["Computer Science, Virginia Tech, Falls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0000-0001-7031-2438","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Falls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103255246","display_name":"Jianfeng He","orcid":"https://orcid.org/0000-0001-8572-4806"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianfeng He","raw_affiliation_strings":["Computer Science, Virginia Tech, Falls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0000-0001-8572-4806","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Falls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102768296","display_name":"Shengkun Wang","orcid":"https://orcid.org/0009-0004-1378-0197"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shengkun Wang","raw_affiliation_strings":["Computer Science, Virginia Tech, Fulls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0009-0004-1378-0197","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Fulls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102893256","display_name":"Min Zhang","orcid":"https://orcid.org/0009-0003-8280-7886"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Computer Science, Virginia Tech, Falls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0009-0003-8280-7886","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Falls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038002204","display_name":"Chang\u2010Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang-Tien Lu","raw_affiliation_strings":["Computer Science, Virginia Tech, Falls Church, Virginia, United States"],"raw_orcid":"https://orcid.org/0000-0003-3675-0199","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Falls Church, Virginia, United States","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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":0.9990000128746033,"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":0.9990000128746033,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.8262584209442139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6769797205924988},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6677902936935425},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6046207547187805},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4931613802909851},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4632742404937744},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36445391178131104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8262584209442139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6769797205924988},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6677902936935425},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6046207547187805},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4931613802909851},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4632742404937744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36445391178131104},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3589132.3625570","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625570","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625570","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/118234","is_oa":true,"landing_page_url":"https://hdl.handle.net/10919/118234","pdf_url":null,"source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article - Refereed"}],"best_oa_location":{"id":"doi:10.1145/3589132.3625570","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625570","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625570","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390100355.pdf","grobid_xml":"https://content.openalex.org/works/W4390100355.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2108598243","https://openalex.org/W2121947440","https://openalex.org/W2138957397","https://openalex.org/W2142796063","https://openalex.org/W2167897892","https://openalex.org/W2194775991","https://openalex.org/W2295475768","https://openalex.org/W2412782625","https://openalex.org/W2480078828","https://openalex.org/W2551751523","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2807974043","https://openalex.org/W2811296358","https://openalex.org/W2886397424","https://openalex.org/W2946862972","https://openalex.org/W2963599420","https://openalex.org/W2963881378","https://openalex.org/W2965383240","https://openalex.org/W2976120863","https://openalex.org/W2990230185","https://openalex.org/W3008156909","https://openalex.org/W3047258141","https://openalex.org/W3102850314","https://openalex.org/W3103092912","https://openalex.org/W3184761517","https://openalex.org/W3205944634","https://openalex.org/W3205981334","https://openalex.org/W4214660208","https://openalex.org/W4312653100","https://openalex.org/W4313150877","https://openalex.org/W4380607244","https://openalex.org/W4385486177","https://openalex.org/W6680396984"],"related_works":["https://openalex.org/W2012531322","https://openalex.org/W2785900585","https://openalex.org/W2353730437","https://openalex.org/W2490303674","https://openalex.org/W2609066826","https://openalex.org/W2810752900","https://openalex.org/W3186538219","https://openalex.org/W2365677836","https://openalex.org/W2531295127","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,11,35,108,169,183],"image":[2,12,48,109,170,184],"semantic":[3,36,110,185],"segmentation":[4,37,130,153],"is":[5,189],"an":[6],"important":[7],"problem":[8],"for":[9,104],"remote":[10,34,107,168,182],"interpretation.":[13],"Although":[14],"remarkable":[15],"progress":[16],"has":[17],"been":[18],"achieved,":[19],"existing":[20,61],"deep":[21],"neural":[22],"network":[23],"methods":[24,64],"suffer":[25],"from":[26,45,67,74],"the":[27,57,82,105,115,135,138,157,162,173],"reliance":[28],"on":[29,71,156,166],"massive":[30],"training":[31],"data.":[32],"Few-shot":[33],"aims":[38],"at":[39,191],"learning":[40,63],"to":[41,79,128,143,149],"segment":[42],"target":[43,58],"objects":[44],"a":[46,51,98,145,151],"query":[47,126,139],"using":[49],"only":[50],"few":[52],"annotated":[53],"support":[54,75,124],"images":[55,127],"of":[56,89,161,177],"class.":[59],"Most":[60],"few-shot":[62,106,181],"stem":[65],"primarily":[66],"their":[68],"sole":[69],"focus":[70],"extracting":[72],"information":[73,160],"images,":[76],"thereby":[77],"failing":[78],"effectively":[80],"address":[81],"large":[83],"variance":[84],"in":[85,180],"appearance":[86],"and":[87,100,121,125,175],"scales":[88],"geographic":[90],"objects.":[91],"To":[92,132],"tackle":[93],"these":[94],"challenges,":[95],"we":[96,141],"propose":[97,142],"Self-Correlation":[99],"Cross-Correlation":[101],"Learning":[102],"Network":[103],"segmentation.":[111,186],"Our":[112],"model":[113,179],"enhances":[114],"generalization":[116],"by":[117],"considering":[118],"both":[119],"self-correlation":[120,136],"cross-correlation":[122],"between":[123],"make":[129],"predictions.":[131],"further":[133],"explore":[134],"with":[137],"image,":[140],"adopt":[144],"classical":[146],"spectral":[147],"method":[148],"produce":[150],"class-agnostic":[152],"mask":[154],"based":[155],"basic":[158],"visual":[159],"image.":[163],"Extensive":[164],"experiments":[165],"two":[167],"datasets":[171],"demonstrate":[172],"effectiveness":[174],"superiority":[176],"our":[178],"The":[187],"code":[188],"available":[190],"https://github.com/linhanwang/SCCNet.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
