{"id":"https://openalex.org/W3127947687","doi":"https://doi.org/10.1109/tmm.2021.3054526","title":"Image Co-Saliency Detection and Instance Co-Segmentation Using Attention Graph Clustering Based Graph Convolutional Network","display_name":"Image Co-Saliency Detection and Instance Co-Segmentation Using Attention Graph Clustering Based Graph Convolutional Network","publication_year":2021,"publication_date":"2021-01-27","ids":{"openalex":"https://openalex.org/W3127947687","doi":"https://doi.org/10.1109/tmm.2021.3054526","mag":"3127947687"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2021.3054526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3054526","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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/A5031499175","display_name":"Tengpeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengpeng Li","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075412755","display_name":"Kaihua Zhang","orcid":"https://orcid.org/0000-0002-1613-3401"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaihua Zhang","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1613-3401","affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103929310","display_name":"Shiwen Shen","orcid":"https://orcid.org/0009-0003-7178-6848"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shiwen Shen","raw_affiliation_strings":["JD Digits, Mountain View, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Digits, Mountain View, California, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461646","display_name":"Bo Liu","orcid":"https://orcid.org/0000-0002-3603-6617"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["JD Digits, Mountain View, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Digits, Mountain View, California, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404959","display_name":"Qingshan Liu","orcid":"https://orcid.org/0000-0002-5512-6984"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingshan Liu","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5512-6984","affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology (B-DAT), and Jiangsu Collaborative Innovation Center on Atmospheric Environment, and Equipment Technology (CICAEET), Nanjing University of Information Science, and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380625","display_name":"Zhu Li","orcid":"https://orcid.org/0000-0002-8246-177X"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhu Li","raw_affiliation_strings":["Department of Computer Science, and Electrical Engnieering (CSEE), University of Missouri, Kansas City, Missouri, USA"],"raw_orcid":"https://orcid.org/0000-0002-8246-177X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, and Electrical Engnieering (CSEE), University of Missouri, Kansas City, Missouri, USA","institution_ids":["https://openalex.org/I75421653"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0946,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.92583238,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"24","issue":null,"first_page":"492","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9944000244140625,"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":0.9825999736785889,"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":0.8283690214157104},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5706956386566162},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5600923895835876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5501263737678528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5304136872291565},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5184761881828308},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4481915831565857},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42008838057518005},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2048124074935913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8283690214157104},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5706956386566162},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5600923895835876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5501263737678528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5304136872291565},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5184761881828308},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4481915831565857},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42008838057518005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2048124074935913},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2021.3054526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3054526","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G441328039","display_name":null,"funder_award_id":"61876088","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5706494817","display_name":null,"funder_award_id":"U20B2065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7375732063","display_name":null,"funder_award_id":"61825601","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":104,"referenced_works":["https://openalex.org/W637153065","https://openalex.org/W1501856433","https://openalex.org/W1507506748","https://openalex.org/W1522301498","https://openalex.org/W1522318187","https://openalex.org/W1556784394","https://openalex.org/W1662382123","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1914179642","https://openalex.org/W1919681008","https://openalex.org/W1919709169","https://openalex.org/W1964884769","https://openalex.org/W1966601141","https://openalex.org/W1971421925","https://openalex.org/W1992992668","https://openalex.org/W1996326832","https://openalex.org/W2037183649","https://openalex.org/W2085625911","https://openalex.org/W2104915577","https://openalex.org/W2108598243","https://openalex.org/W2116341502","https://openalex.org/W2121947440","https://openalex.org/W2135957668","https://openalex.org/W2151103935","https://openalex.org/W2159692873","https://openalex.org/W2166914830","https://openalex.org/W2194775991","https://openalex.org/W2216125271","https://openalex.org/W2278868814","https://openalex.org/W2323404866","https://openalex.org/W2344340558","https://openalex.org/W2358876993","https://openalex.org/W2403333215","https://openalex.org/W2415053570","https://openalex.org/W2486722903","https://openalex.org/W2529603763","https://openalex.org/W2565639579","https://openalex.org/W2604942799","https://openalex.org/W2605929543","https://openalex.org/W2615981376","https://openalex.org/W2744613561","https://openalex.org/W2776622059","https://openalex.org/W2786297715","https://openalex.org/W2792965491","https://openalex.org/W2793668851","https://openalex.org/W2806331055","https://openalex.org/W2886970679","https://openalex.org/W2889081631","https://openalex.org/W2891177538","https://openalex.org/W2895136135","https://openalex.org/W2895251968","https://openalex.org/W2896535068","https://openalex.org/W2901412525","https://openalex.org/W2902609089","https://openalex.org/W2904945062","https://openalex.org/W2907492528","https://openalex.org/W2948300571","https://openalex.org/W2954275231","https://openalex.org/W2962849746","https://openalex.org/W2963017945","https://openalex.org/W2963076818","https://openalex.org/W2963091558","https://openalex.org/W2963150697","https://openalex.org/W2963281829","https://openalex.org/W2963311325","https://openalex.org/W2963529609","https://openalex.org/W2963572583","https://openalex.org/W2963598268","https://openalex.org/W2963834057","https://openalex.org/W2963868681","https://openalex.org/W2963915286","https://openalex.org/W2964015378","https://openalex.org/W2964028976","https://openalex.org/W2964051675","https://openalex.org/W2964094751","https://openalex.org/W2964732194","https://openalex.org/W2965638232","https://openalex.org/W2969575296","https://openalex.org/W2972209102","https://openalex.org/W2972640707","https://openalex.org/W2972705427","https://openalex.org/W2979683452","https://openalex.org/W2981680738","https://openalex.org/W2987391422","https://openalex.org/W2994041372","https://openalex.org/W3010616503","https://openalex.org/W3029368604","https://openalex.org/W3030079400","https://openalex.org/W3034499925","https://openalex.org/W3035074791","https://openalex.org/W3035284915","https://openalex.org/W3035666869","https://openalex.org/W3096289386","https://openalex.org/W3108608656","https://openalex.org/W3152893301","https://openalex.org/W6620673361","https://openalex.org/W6631190155","https://openalex.org/W6637178625","https://openalex.org/W6637373629","https://openalex.org/W6713582119","https://openalex.org/W6719270105","https://openalex.org/W6720006811","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2121910908"],"abstract_inverted_index":{"Co-Saliency":[0],"Detection":[1],"(CSD)":[2],"is":[3],"to":[4,23,83,87,102,124,164],"explore":[5],"the":[6,89,104,129,155,160],"concurrent":[7],"patterns":[8],"and":[9,25,60,65,91,127,136,153,159,172,185,187,196,198],"salient":[10,105,147],"objects":[11,107],"from":[12,108],"a":[13,47,78,118,146],"group":[14],"of":[15,29,157],"relevant":[16],"images,":[17],"while":[18],"Instance":[19],"Co-Segmentation":[20],"(ICS)":[21],"aims":[22],"identify":[24],"segment":[26],"out":[27],"all":[28],"these":[30,42],"co-salient":[31],"instances,":[32],"generating":[33],"corresponding":[34],"mask":[35],"for":[36,58,151],"each":[37],"instance.":[38],"To":[39],"simultaneously":[40],"tackle":[41],"two":[43],"tasks,":[44],"we":[45,76,95,116,144],"present":[46,117],"novel":[48],"adaptive":[49],"graph":[50,55,79,99,130,134],"convolutional":[51,80,131],"network":[52,81,150],"with":[53,121],"attention":[54,98,133],"clustering":[56,100],"(GCAGC)":[57],"CSD":[59,137,179],"ICS,":[61],"termed":[62],"as":[63],"GCAGC-CSD":[64,69,158,171],"GCAGC-ICS,":[66,152],"respectively.":[67],"The":[68,169],"contains":[70],"three":[71],"key":[72],"model":[73],"designs:":[74],"first,":[75],"develop":[77],"architecture":[82],"extract":[84],"multi-scale":[85],"representations":[86],"characterize":[88],"intra-":[90],"inter-image":[92],"consistency.":[93],"Second,":[94],"propose":[96],"an":[97,112,140],"algorithm":[101],"distinguish":[103],"foreground":[106],"common":[109],"areas":[110],"in":[111,139],"unsupervised":[113],"manner.":[114],"Third,":[115],"unified":[119],"framework":[120],"encoder-decoder":[122],"structure":[123],"jointly":[125],"train":[126],"optimize":[128],"network,":[132],"cluster,":[135],"decoder":[138],"end-to-end":[141],"fashion.":[142],"Afterwards,":[143],"design":[145],"instance":[148,161],"segmentation":[149,162],"combine":[154],"outputs":[156],"branch":[163],"obtain":[165],"instance-aware":[166],"co-segmentation":[167],"masks.":[168],"proposed":[170],"GCAGC-ICS":[173],"are":[174],"extensively":[175],"evaluated":[176],"on":[177,204],"four":[178],"benchmark":[180,190],"datasets":[181,191],"(iCoseg,":[182],"Cosal2015,":[183],"COCO-SEG":[184],"CoSOD3k)":[186],"five":[188],"ICS":[189],"(CoSOD3k,":[192],"COCO-NONVOC,":[193],"COCO-VOC,":[194],"VOC12":[195],"SOC),":[197],"achieve":[199],"superior":[200],"performance":[201],"over":[202],"state-of-the-arts":[203],"both":[205],"tasks.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}