{"id":"https://openalex.org/W4224919524","doi":"https://doi.org/10.1109/icassp43922.2022.9747509","title":"Pseudo-Interacting Guided Network for Few-Shot Segmentation","display_name":"Pseudo-Interacting Guided Network for Few-Shot Segmentation","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224919524","doi":"https://doi.org/10.1109/icassp43922.2022.9747509"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747509","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5014932626","display_name":"Xiaoliu Luo","orcid":"https://orcid.org/0000-0002-2365-4950"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliu Luo","raw_affiliation_strings":["Chongqing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074624879","display_name":"Jing Luo","orcid":"https://orcid.org/0000-0002-6230-8989"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Luo","raw_affiliation_strings":["Zhengzhou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhengzhou University","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015214891","display_name":"Zhao Duan","orcid":"https://orcid.org/0000-0001-6783-7727"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Duan","raw_affiliation_strings":["Chongqing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035567238","display_name":"Jin Tan","orcid":"https://orcid.org/0000-0001-6550-964X"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Tan","raw_affiliation_strings":["Chongqing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101664915","display_name":"Taiping Zhang","orcid":"https://orcid.org/0000-0001-9891-4203"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taiping Zhang","raw_affiliation_strings":["Chongqing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"2365","last_page":"2369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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":0.9987999796867371,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7539969682693481},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7293404340744019},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6439557671546936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6379156708717346},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5266554355621338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4900011122226715},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47782400250434875},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45474833250045776},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4536435604095459},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4502038359642029},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40786534547805786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1784285008907318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7539969682693481},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7293404340744019},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6439557671546936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6379156708717346},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5266554355621338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4900011122226715},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47782400250434875},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45474833250045776},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4536435604095459},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4502038359642029},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40786534547805786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1784285008907318},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747509","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2395611524","https://openalex.org/W2560023338","https://openalex.org/W2601564443","https://openalex.org/W2897139960","https://openalex.org/W2902683551","https://openalex.org/W2916916867","https://openalex.org/W2963078159","https://openalex.org/W2963091558","https://openalex.org/W2963599420","https://openalex.org/W2964309882","https://openalex.org/W2981787211","https://openalex.org/W2981899103","https://openalex.org/W2983850069","https://openalex.org/W2990230185","https://openalex.org/W2994528761","https://openalex.org/W3034674637","https://openalex.org/W3034985049","https://openalex.org/W3047258141","https://openalex.org/W3049410041","https://openalex.org/W3093412994","https://openalex.org/W3106906018","https://openalex.org/W3108187451","https://openalex.org/W3108189450","https://openalex.org/W3167559252","https://openalex.org/W3176065502","https://openalex.org/W6640054144","https://openalex.org/W6744114936","https://openalex.org/W6755593459","https://openalex.org/W6756657096","https://openalex.org/W6780309945","https://openalex.org/W6781222066","https://openalex.org/W6781810510","https://openalex.org/W6786471941"],"related_works":["https://openalex.org/W4376620596","https://openalex.org/W3177249605","https://openalex.org/W2534152068","https://openalex.org/W3138508047","https://openalex.org/W1972515067","https://openalex.org/W1689909837","https://openalex.org/W4293054914","https://openalex.org/W4298525700","https://openalex.org/W2953362004","https://openalex.org/W2549121492"],"abstract_inverted_index":{"Few-shot":[0],"segmentation":[1],"has":[2],"got":[3],"a":[4,20,34,112,117,122,137,154],"lot":[5],"of":[6,29,52,75,143,182],"concerns":[7],"recently.":[8],"Existing":[9],"methods":[10,195],"mainly":[11],"locate":[12],"and":[13,48,55,63,93,178,202],"recognize":[14],"the":[15,72,76,80,90,104,131,141,148,171,175,180,183],"target":[16,26,87,101,149,172],"object":[17,27,173],"based":[18,165],"on":[19,166,196],"cross-guided":[21,119,133,184],"way":[22],"that":[23,115,139,190],"applies":[24,159],"masked":[25],"features":[28],"support(query)":[30],"images":[31,47,50],"to":[32,61,70,78,84,97,135,147,169],"make":[33],"feature":[35],"matching":[36],"with":[37,121,162],"query(support)":[38],"images.":[39],"However,":[40],"there":[41],"are":[42],"some":[43,86,160],"differences":[44],"between":[45],"support":[46],"query":[49,91,105,176],"because":[51],"large":[53],"appearance":[54],"scale":[56],"variation,":[57],"which":[58,158],"will":[59],"lead":[60],"inaccurate":[62],"incomplete":[64],"segmentation.":[65,81],"This":[66],"problem":[67],"inspired":[68],"us":[69],"explore":[71],"local":[73],"coherence":[74],"image":[77,92,177],"guide":[79],"We":[82],"try":[83],"get":[85],"pixels":[88,96,102,161],"in":[89,103,174],"apply":[94],"these":[95],"search":[98],"for":[99],"more":[100],"image.":[106],"In":[107],"this":[108],"work,":[109],"we":[110,128,152],"propose":[111],"novel":[113],"network":[114],"combines":[116],"universal":[118,132],"branch":[120,134,185],"new":[123],"pseudo-interacting":[124,155],"guided":[125,156],"branch.":[126],"Specifically,":[127],"first":[129],"employ":[130],"produce":[136],"pseudo-labeling":[138,168],"represents":[140],"probability":[142],"each":[144],"pixel":[145],"belonging":[146],"object.":[150],"Then":[151],"design":[153],"branch,":[157],"high":[163],"probabilities":[164],"generated":[167],"segment":[170],"revises":[179],"results":[181],"simultaneously.":[186],"Extensive":[187],"experiments":[188],"show":[189],"our":[191],"approach":[192],"outperforms":[193],"state-of-the-art":[194],"both":[197],"PASCAL-5":[198],"<sup":[199,204],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[200,205],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</sup>":[201,206],"COCO-20":[203],"datasets.":[207]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
