{"id":"https://openalex.org/W4402981482","doi":"https://doi.org/10.1109/icme57554.2024.10687619","title":"Prototype-Guided Prior Enhancement and Rectification in Few-shot Semantic Segmentation","display_name":"Prototype-Guided Prior Enhancement and Rectification in Few-shot Semantic Segmentation","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402981482","doi":"https://doi.org/10.1109/icme57554.2024.10687619"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687619","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101807196","display_name":"Yiming Tang","orcid":"https://orcid.org/0000-0003-2871-2299"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiming Tang","raw_affiliation_strings":["Fudan University,School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100745222","display_name":"Yi Yu","orcid":"https://orcid.org/0000-0002-0294-6620"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yi Yu","raw_affiliation_strings":["Hiroshima University,Graduate School of Advanced Science and Engineering,Hiroshima,Japan"],"affiliations":[{"raw_affiliation_string":"Hiroshima University,Graduate School of Advanced Science and Engineering,Hiroshima,Japan","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108473021","display_name":"Yan Qiu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Qiu Chen","raw_affiliation_strings":["Fudan University,School of Computer Science,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101807196"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14626585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"PP","issue":null,"first_page":"1","last_page":"6"},"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":0.9955000281333923,"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":0.9955000281333923,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9840999841690063,"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9757999777793884,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.7410187721252441},{"id":"https://openalex.org/keywords/rectification","display_name":"Rectification","score":0.7327916622161865},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6952258944511414},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6365475058555603},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6053612232208252},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5811526775360107},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.43518924713134766},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1213555634021759},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.0759190022945404},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07473057508468628}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7410187721252441},{"id":"https://openalex.org/C50942859","wikidata":"https://www.wikidata.org/wiki/Q4967193","display_name":"Rectification","level":3,"score":0.7327916622161865},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6952258944511414},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6365475058555603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6053612232208252},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5811526775360107},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.43518924713134766},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1213555634021759},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0759190022945404},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07473057508468628},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10687619","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2144794286","https://openalex.org/W2412782625","https://openalex.org/W2752782242","https://openalex.org/W2963078159","https://openalex.org/W2981787211","https://openalex.org/W3092663126","https://openalex.org/W3096609285","https://openalex.org/W3106906018","https://openalex.org/W3167559252","https://openalex.org/W4224860128","https://openalex.org/W4312635568","https://openalex.org/W4386075526","https://openalex.org/W4386159906","https://openalex.org/W6784333009","https://openalex.org/W6793652844","https://openalex.org/W6794582915","https://openalex.org/W6795934563"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W4294892107","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"Few-shot":[0],"segmentation":[1],"aims":[2],"to":[3,55,66,99,105,116],"recognize":[4],"unseen":[5],"objects":[6],"from":[7,52,93],"a":[8,21,25,45],"few":[9],"examples":[10],"per":[11],"class.":[12],"It":[13],"divides":[14],"the":[15,35,76,106,122,151],"training":[16],"process":[17],"into":[18],"episodes":[19],"with":[20],"support":[22,29,53],"set":[23,30,37],"and":[24,34,79,111,160],"query":[26,36,58],"set.":[27],"The":[28,127],"provides":[31],"annotated":[32],"examples,":[33],"contains":[38],"images":[39,54],"for":[40],"annotation.":[41],"Most":[42],"models":[43,68],"follow":[44],"prototypical":[46],"approach,":[47],"which":[48,73,114],"extracts":[49],"representative":[50,158],"prototypes":[51],"compare":[56],"against":[57],"image":[59],"features.":[60,95],"PFENet":[61],"proposed":[62],"using":[63],"prior":[64],"maps":[65],"focus":[67,149],"on":[69,150],"likely":[70],"foreground":[71,125],"areas,":[72],"effectively":[74],"improves":[75],"model\u2019s":[77],"performance":[78,119],"is":[80],"widely":[81],"used":[82],"in":[83,120,141],"subsequent":[84],"methods.":[85],"However,":[86],"existing":[87],"prior-based":[88],"techniques":[89],"solely":[90],"derive":[91],"priors":[92,131,146],"high-level":[94,130,145],"High-level":[96],"features":[97],"tend":[98],"lack":[100],"detailed":[101],"structure":[102],"information":[103],"due":[104],"cumulative":[107],"effects":[108],"of":[109,124,129],"convolutions":[110],"pooling":[112],"operations,":[113],"leads":[115],"their":[117],"poor":[118],"recognizing":[121],"boundaries":[123,133],"areas.":[126],"uncertainty":[128],"near":[132],"may":[134],"erroneously":[135],"introduce":[136],"category-irrelevant":[137],"noise,":[138],"as":[139],"shown":[140],"Fig.":[142],"1.":[143],"Moreover,":[144],"often":[147],"overly":[148],"most":[152],"relevant":[153],"parts,":[154],"potentially":[155],"overlooking":[156],"other":[157],"structures":[159],"losing":[161],"semantic":[162],"cues.":[163]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
