{"id":"https://openalex.org/W4220971618","doi":"https://doi.org/10.1109/tnnls.2022.3155486","title":"A Mutually Supervised Graph Attention Network for Few-Shot Segmentation: The Perspective of Fully Utilizing Limited Samples","display_name":"A Mutually Supervised Graph Attention Network for Few-Shot Segmentation: The Perspective of Fully Utilizing Limited Samples","publication_year":2022,"publication_date":"2022-03-14","ids":{"openalex":"https://openalex.org/W4220971618","doi":"https://doi.org/10.1109/tnnls.2022.3155486","pmid":"https://pubmed.ncbi.nlm.nih.gov/35286269"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3155486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3155486","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Honghao Gao","orcid":"https://orcid.org/0000-0001-6861-9684"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honghao Gao","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6861-9684","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Junsheng Xiao","orcid":"https://orcid.org/0000-0002-7781-856X"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junsheng Xiao","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7781-856X","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuyu Yin","orcid":"https://orcid.org/0000-0001-7565-4111"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyu Yin","raw_affiliation_strings":["College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7565-4111","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tong Liu","orcid":"https://orcid.org/0000-0003-0485-839X"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Liu","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0485-839X","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jiangang Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089783","display_name":"Shanghai Medical Information Center","ror":"https://ror.org/007wz9933","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089783"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangang Shi","raw_affiliation_strings":["Shanghai Shangda Hairun Information System Company Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Shangda Hairun Information System Company Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210089783"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.4886,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.99245448,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"35","issue":"4","first_page":"4826","last_page":"4838"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6449999809265137,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6449999809265137,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.09220000356435776,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.08110000193119049,"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/pascal","display_name":"Pascal (unit)","score":0.730400025844574},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5543000102043152},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.516700029373169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5078999996185303},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4821999967098236},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45179998874664307},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43380001187324524},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.3817000091075897},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3732999861240387}],"concepts":[{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.730400025844574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6970999836921692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5719000101089478},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5543000102043152},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.516700029373169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45179998874664307},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.3817000091075897},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30559998750686646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3001999855041504},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.27889999747276306},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.27239999175071716},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2522999942302704},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3155486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3155486","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35286269","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35286269","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W611457968","https://openalex.org/W1542791059","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2088049833","https://openalex.org/W2117539524","https://openalex.org/W2123229215","https://openalex.org/W2133515615","https://openalex.org/W2194321275","https://openalex.org/W2295107390","https://openalex.org/W2306289963","https://openalex.org/W2337429362","https://openalex.org/W2412782625","https://openalex.org/W2600144439","https://openalex.org/W2607394097","https://openalex.org/W2625674597","https://openalex.org/W2799124825","https://openalex.org/W2895340641","https://openalex.org/W2903655137","https://openalex.org/W2962810718","https://openalex.org/W2963078159","https://openalex.org/W2963599420","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2964105864","https://openalex.org/W2965729941","https://openalex.org/W2983850069","https://openalex.org/W2986732100","https://openalex.org/W2990230185","https://openalex.org/W3021853564","https://openalex.org/W3033502887","https://openalex.org/W3034312118","https://openalex.org/W3046698617","https://openalex.org/W3047258141","https://openalex.org/W3108187451","https://openalex.org/W3128992469","https://openalex.org/W4300479382","https://openalex.org/W6637606113","https://openalex.org/W6640295612","https://openalex.org/W6717697761","https://openalex.org/W6736057607","https://openalex.org/W6746260573","https://openalex.org/W6747943641","https://openalex.org/W6756657096","https://openalex.org/W6773666150","https://openalex.org/W6783596713","https://openalex.org/W6784596683","https://openalex.org/W6799265008"],"related_works":[],"abstract_inverted_index":{"Fully":[0],"supervised":[1,71,158],"semantic":[2],"segmentation":[3,29,73],"has":[4,30],"performed":[5],"well":[6],"in":[7,66,125],"many":[8],"computer":[9],"vision":[10],"tasks.":[11],"However,":[12,54],"it":[13,41],"is":[14,75,112,143],"time-consuming":[15],"because":[16],"training":[17],"a":[18,21,33,44,69,104,156],"model":[19],"requires":[20,42],"large":[22],"number":[23,122],"of":[24,46,58,91,123,139,164,207],"pixel-level":[25],"annotated":[26,47],"samples.":[27],"Few-shot":[28],"recently":[31],"become":[32],"popular":[34],"approach":[35],"to":[36,49,51,87,114,129,148,177],"addressing":[37],"this":[38,67],"problem,":[39],"as":[40,145],"only":[43],"handful":[45],"samples":[48,60],"generalize":[50],"new":[52],"categories.":[53,181],"the":[55,78,89,95,108,121,126,131,136,140,150,161,165,173,179,186,199,202],"full":[56],"utilization":[57],"limited":[59],"remains":[61],"an":[62],"open":[63],"problem.":[64],"Thus,":[65],"article,":[68],"mutually":[70,157],"few-shot":[72],"network":[74,111],"proposed.":[76],"First,":[77],"feature":[79,92],"maps":[80,163],"from":[81],"intermediate":[82,166],"convolution":[83],"layers":[84,167],"are":[85,101,168,183],"fused":[86,169],"enrich":[88],"capacity":[90],"representation.":[93],"Second,":[94],"support":[96,127,151],"image":[97,100,128,133,142,152],"and":[98,107,119,170,195,198,204],"query":[99,132,141],"combined":[102],"into":[103,172],"bipartite":[105],"graph,":[106],"graph":[109,174],"attention":[110,137,162],"adopted":[113],"avoid":[115],"losing":[116],"spatial":[117],"information":[118,147],"increase":[120],"pixels":[124],"guide":[130],"segmentation.":[134],"Third,":[135],"map":[138],"used":[144],"prior":[146],"enhance":[149],"segmentation,":[153],"which":[154],"forms":[155],"regime.":[159],"Finally,":[160],"sent":[171],"reasoning":[175],"layer":[176],"infer":[178],"pixel":[180],"Experiments":[182],"conducted":[184],"on":[185],"PASCAL":[187],"VOC-":[188],"<formula":[189],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[190],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[191],"<tex>$5^i$</tex>":[192],"</formula>":[193],"dataset":[194],"FSS-1000":[196],"dataset,":[197],"results":[200],"demonstrate":[201],"effectiveness":[203],"superior":[205],"performance":[206],"our":[208],"method":[209],"compared":[210],"with":[211],"other":[212],"baseline":[213],"methods.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":54},{"year":2022,"cited_by_count":24}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2022-04-03T00:00:00"}
