{"id":"https://openalex.org/W4312287801","doi":"https://doi.org/10.1109/tcsvt.2022.3225865","title":"TCNet: Co-Salient Object Detection via Parallel Interaction of Transformers and CNNs","display_name":"TCNet: Co-Salient Object Detection via Parallel Interaction of Transformers and CNNs","publication_year":2022,"publication_date":"2022-12-01","ids":{"openalex":"https://openalex.org/W4312287801","doi":"https://doi.org/10.1109/tcsvt.2022.3225865"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2022.3225865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3225865","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5061190949","display_name":"Yanliang Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I921716337","display_name":"Northeast Petroleum University","ror":"https://ror.org/03net5943","country_code":"CN","type":"education","lineage":["https://openalex.org/I921716337"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanliang Ge","raw_affiliation_strings":["School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China","institution_ids":["https://openalex.org/I921716337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357522","display_name":"Qiao Zhang","orcid":"https://orcid.org/0000-0002-3509-8103"},"institutions":[{"id":"https://openalex.org/I921716337","display_name":"Northeast Petroleum University","ror":"https://ror.org/03net5943","country_code":"CN","type":"education","lineage":["https://openalex.org/I921716337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Zhang","raw_affiliation_strings":["School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China","institution_ids":["https://openalex.org/I921716337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085828297","display_name":"Tian-Zhu Xiang","orcid":"https://orcid.org/0000-0002-3321-1993"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Tian-Zhu Xiang","raw_affiliation_strings":["Inception Institute of Artificial Intelligence and G42 Bayanat, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence and G42 Bayanat, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210116052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054518730","display_name":"Cong Zhang","orcid":"https://orcid.org/0000-0002-8952-0429"},"institutions":[{"id":"https://openalex.org/I921716337","display_name":"Northeast Petroleum University","ror":"https://ror.org/03net5943","country_code":"CN","type":"education","lineage":["https://openalex.org/I921716337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Zhang","raw_affiliation_strings":["School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China","institution_ids":["https://openalex.org/I921716337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013301642","display_name":"Hongbo Bi","orcid":"https://orcid.org/0000-0003-2442-330X"},"institutions":[{"id":"https://openalex.org/I921716337","display_name":"Northeast Petroleum University","ror":"https://ror.org/03net5943","country_code":"CN","type":"education","lineage":["https://openalex.org/I921716337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbo Bi","raw_affiliation_strings":["School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Information, Northeast Petroleum University, Daqing, China","institution_ids":["https://openalex.org/I921716337"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5061190949"],"corresponding_institution_ids":["https://openalex.org/I921716337"],"apc_list":null,"apc_paid":null,"fwci":5.3998,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.9696242,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"33","issue":"6","first_page":"2600","last_page":"2615"},"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":0.9793000221252441,"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/T11094","display_name":"Face Recognition and Perception","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.749114990234375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6166121363639832},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.605383574962616},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5795788764953613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5283575654029846},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5167562365531921},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48895418643951416},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.45086345076560974},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33271533250808716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.749114990234375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6166121363639832},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.605383574962616},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5795788764953613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5283575654029846},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5167562365531921},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48895418643951416},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.45086345076560974},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33271533250808716}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2022.3225865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2022.3225865","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G6544215039","display_name":null,"funder_award_id":"LH2022F005","funder_id":"https://openalex.org/F4320323085","funder_display_name":"Natural Science Foundation of Heilongjiang Province"}],"funders":[{"id":"https://openalex.org/F4320323085","display_name":"Natural Science Foundation of Heilongjiang Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":116,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1914179642","https://openalex.org/W1964884769","https://openalex.org/W1992992668","https://openalex.org/W2037183649","https://openalex.org/W2100470808","https://openalex.org/W2141303268","https://openalex.org/W2153760331","https://openalex.org/W2156777442","https://openalex.org/W2342491128","https://openalex.org/W2358876993","https://openalex.org/W2403333215","https://openalex.org/W2518666399","https://openalex.org/W2529603763","https://openalex.org/W2565639579","https://openalex.org/W2605793178","https://openalex.org/W2615981376","https://openalex.org/W2740667773","https://openalex.org/W2752782242","https://openalex.org/W2766912043","https://openalex.org/W2767623212","https://openalex.org/W2786297715","https://openalex.org/W2789646185","https://openalex.org/W2793668851","https://openalex.org/W2884585870","https://openalex.org/W2904945062","https://openalex.org/W2937582268","https://openalex.org/W2946824329","https://openalex.org/W2954275231","https://openalex.org/W2955058313","https://openalex.org/W2963112696","https://openalex.org/W2963529609","https://openalex.org/W2963572583","https://openalex.org/W2963868681","https://openalex.org/W2964429685","https://openalex.org/W2972640707","https://openalex.org/W2972705427","https://openalex.org/W2981680738","https://openalex.org/W2987701848","https://openalex.org/W2990984982","https://openalex.org/W2991366018","https://openalex.org/W2997316506","https://openalex.org/W2998449272","https://openalex.org/W3023562424","https://openalex.org/W3034499925","https://openalex.org/W3034552520","https://openalex.org/W3035422681","https://openalex.org/W3035666869","https://openalex.org/W3039991645","https://openalex.org/W3096289386","https://openalex.org/W3096609285","https://openalex.org/W3101633331","https://openalex.org/W3105290831","https://openalex.org/W3105291825","https://openalex.org/W3108025068","https://openalex.org/W3121523901","https://openalex.org/W3131500599","https://openalex.org/W3132890542","https://openalex.org/W3138516171","https://openalex.org/W3159886901","https://openalex.org/W3160694286","https://openalex.org/W3163735346","https://openalex.org/W3164098653","https://openalex.org/W3171125843","https://openalex.org/W3173349970","https://openalex.org/W3174178235","https://openalex.org/W3175515048","https://openalex.org/W3181330405","https://openalex.org/W3194576372","https://openalex.org/W3202242435","https://openalex.org/W3202407433","https://openalex.org/W3207668590","https://openalex.org/W3211490618","https://openalex.org/W3214586131","https://openalex.org/W3216049821","https://openalex.org/W4205288538","https://openalex.org/W4211256032","https://openalex.org/W4214561053","https://openalex.org/W4214680709","https://openalex.org/W4214736485","https://openalex.org/W4221145551","https://openalex.org/W4221161499","https://openalex.org/W4224330024","https://openalex.org/W4225309741","https://openalex.org/W4239147634","https://openalex.org/W4287204411","https://openalex.org/W4295312788","https://openalex.org/W4295528401","https://openalex.org/W4306167843","https://openalex.org/W4309721374","https://openalex.org/W4362654014","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6739901393","https://openalex.org/W6753412334","https://openalex.org/W6766978945","https://openalex.org/W6778485988","https://openalex.org/W6780226713","https://openalex.org/W6783730298","https://openalex.org/W6785161788","https://openalex.org/W6785582761","https://openalex.org/W6790703111","https://openalex.org/W6791388874","https://openalex.org/W6794904954","https://openalex.org/W6797399245","https://openalex.org/W6800759316","https://openalex.org/W6804931533","https://openalex.org/W6806029610","https://openalex.org/W6810081451","https://openalex.org/W6810464507","https://openalex.org/W6840571137","https://openalex.org/W6847109930"],"related_works":["https://openalex.org/W3038672259","https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W4312376745","https://openalex.org/W3135818718","https://openalex.org/W2801801420","https://openalex.org/W2767651786","https://openalex.org/W2144059113","https://openalex.org/W3003836766","https://openalex.org/W1964120219"],"abstract_inverted_index":{"The":[0,198],"purpose":[1],"of":[2,18,104,142,153,156,171,180],"co-salient":[3,227],"object":[4,228],"detection":[5],"(CoSOD)":[6],"is":[7,45,56,164,186,201,219],"to":[8,58,134,166,188,221],"detect":[9],"the":[10,50,53,76,101,115,120,126,136,150,169,181],"salient":[11],"objects":[12],"that":[13,215],"co-occur":[14],"in":[15,29,39],"a":[16,81,147],"group":[17,127,190],"relevant":[19],"images.":[20],"CoSOD":[21,206],"has":[22],"been":[23],"significantly":[24],"prospered":[25],"by":[26],"recent":[27],"advances":[28],"convolutional":[30],"neural":[31],"networks":[32],"(CNNs).":[33],"However,":[34],"it":[35,109],"shows":[36],"general":[37],"limitations":[38],"modeling":[40],"long-range":[41],"feature":[42,191],"dependencies,":[43],"which":[44,68,87],"crucial":[46],"for":[47,72,97,149,226],"CoSOD.":[48,73],"In":[49],"vision":[51],"transformer,":[52],"self-attention":[54],"mechanism":[55],"utilized":[57],"capture":[59,135],"global":[60,95,137,175],"dependencies":[61],"but":[62],"unfortunately":[63],"destroy":[64],"local":[65,92,172],"spatial":[66],"details,":[67],"are":[69],"also":[70],"essential":[71],"To":[74],"address":[75],"above":[77],"issues,":[78],"we":[79],"propose":[80],"dual":[82],"network":[83],"structure,":[84],"called":[85],"TCNet,":[86],"can":[88],"efficiently":[89],"excavate":[90],"both":[91,157],"information":[93,173],"and":[94,106,125,174,193],"representations":[96],"co-saliency":[98,196],"learning":[99],"via":[100],"parallel":[102],"interaction":[103],"Transformers":[105],"CNNs.":[107],"Specifically,":[108],"contains":[110],"three":[111],"critical":[112],"components,":[113],"i.e.,":[114],"mutual":[116],"consensus":[117,121,138,154,170],"module":[118,123],"(MCM),":[119],"complementary":[122],"(CCM),":[124],"consistent":[128],"progressive":[129],"decoder":[130],"(GCPD).":[131],"MCM":[132],"aims":[133],"from":[139,177],"high-level":[140],"features":[141],"these":[143],"two":[144,182],"branches":[145,158],"as":[146],"guide":[148],"following":[151],"integration":[152],"cues":[155],"at":[159],"each":[160],"level.":[161],"Next,":[162],"CCM":[163],"designed":[165],"effectively":[167],"fuse":[168],"contexts":[176],"different":[178],"levels":[179],"branches.":[183],"Finally,":[184],"GCPD":[185],"developed":[187],"maintain":[189],"consistency":[192],"predict":[194],"accurate":[195],"maps.":[197],"proposed":[199,217],"TCNet":[200],"evaluated":[202],"on":[203],"five":[204],"challenging":[205],"benchmark":[207],"datasets":[208],"using":[209],"six":[210],"widely":[211],"used":[212],"metrics,":[213],"showing":[214],"our":[216],"method":[218],"superior":[220],"other":[222],"existing":[223],"cutting-edge":[224],"methods":[225],"detection.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":8}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}