{"id":"https://openalex.org/W7155011533","doi":"https://doi.org/10.1109/tip.2026.3683590","title":"Toward Adaptive Open-Set Object Detection via Category-Level Collaboration Knowledge Mining","display_name":"Toward Adaptive Open-Set Object Detection via Category-Level Collaboration Knowledge Mining","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7155011533","doi":"https://doi.org/10.1109/tip.2026.3683590","pmid":"https://pubmed.ncbi.nlm.nih.gov/42009328"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3683590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3683590","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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":"https://openalex.org/A5134083135","display_name":"Yuqi Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Ji","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0005-6543-324X","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030485695","display_name":"Junjie Ke","orcid":"https://orcid.org/0000-0001-8512-3744"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Ke","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-8512-3744","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039837634","display_name":"Lihuo He","orcid":"https://orcid.org/0000-0002-0555-3574"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihuo He","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0555-3574","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065096406","display_name":"L Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhi Wang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1953-3339","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0002-7985-0037"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-7985-0037","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.1051,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98170015,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"35","issue":null,"first_page":"4134","last_page":"4148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.23749999701976776,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.23749999701976776,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.05009999871253967,"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":0.049300000071525574,"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/object-detection","display_name":"Object detection","score":0.6144999861717224},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42080000042915344},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.38830000162124634},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.38269999623298645},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.36800000071525574},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.34700000286102295},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.33869999647140503},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6144999861717224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45260000228881836},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4041999876499176},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.38830000162124634},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36640000343322754},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.33869999647140503},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C2776088427","wikidata":"https://www.wikidata.org/wiki/Q378859","display_name":"Pattern detection","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.2946000099182129},{"id":"https://openalex.org/C2775966667","wikidata":"https://www.wikidata.org/wiki/Q6423384","display_name":"Knowledge modeling","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.257099986076355}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3683590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3683590","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:42009328","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42009328","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G463811269","display_name":null,"funder_award_id":"62276203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G913836228","display_name":null,"funder_award_id":"62036007","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"object":[1,26,204],"detection":[2,27],"methods":[3],"struggle":[4],"to":[5,14,47,99,119,172,176,201,221,227,237,249,276],"generalize":[6],"across":[7,108],"increasingly":[8],"data":[9],"domains":[10],"while":[11,43],"simultaneously":[12],"adapting":[13],"the":[15,40,54,82,151,180,185,188,203,207,223,228,232,263],"emergence":[16],"of":[17,153,209,234,274],"novel":[18,51,75,177,189,210],"categories.":[19,211],"To":[20,85],"tackle":[21],"this":[22,89],"challenge,":[23],"adaptive":[24,214],"open-set":[25],"(AOOD)":[28],"has":[29],"been":[30],"introduced,":[31],"which":[32,149],"employs":[33],"supervised":[34],"training":[35],"on":[36,257],"base":[37,49,193],"categories":[38,52,178,190],"within":[39,179],"source":[41,83,181,251],"domain":[42,182,252,259],"enabling":[44,231],"unsupervised":[45,147],"adaptation":[46],"both":[48,102],"and":[50,77,104,127,156,191],"in":[53,74],"target":[55,229],"domain.":[56,84],"However,":[57],"existing":[58],"AOOD":[59,269],"approaches":[60],"are":[61,198],"still":[62],"hindered":[63],"by":[64,183],"several":[65],"limitations,":[66],"including":[67],"insufficient":[68],"cross-domain":[69,161],"feature":[70,79,106,215],"representation,":[71],"inter-category":[72],"ambiguity":[73],"classes,":[76],"inherent":[78],"bias":[80],"toward":[81],"overcome":[86],"these":[87,246],"issues,":[88],"paper":[90],"proposes":[91],"a":[92,111,137,165],"category-level":[93,134,225],"collaboration":[94],"knowledge":[95,135,162,226],"mining":[96],"strategy":[97,218],"designed":[98,171],"comprehensively":[100],"exploit":[101],"inter-class":[103],"intra-class":[105,128],"relationships":[107,155,186],"domains.":[109],"Specifically,":[110],"clustering-based":[112],"memory":[113,139,240],"bank":[114,241],"(CMB)":[115],"is":[116,143,170,219,242,280],"initially":[117],"constructed":[118],"aggregate":[120],"class":[121,124],"prototype":[122],"features,":[123,126,130],"auxiliary":[125],"disparity":[129],"thereby":[131],"embedding":[132],"rich":[133],"into":[136],"unified":[138],"structure.":[140],"The":[141,195,239],"CMB":[142],"iteratively":[144],"updated":[145,243],"through":[146],"clustering,":[148],"facilitates":[150],"modeling":[152],"intra-category":[154],"enhances":[157],"its":[158],"capacity":[159],"for":[160,206],"representation.":[163],"Subsequently,":[164],"base-to-novel":[166],"selection":[167],"metric":[168],"(BNSM)":[169],"identify":[173],"features":[174,197,248],"corresponding":[175],"regulating":[184],"between":[187],"each":[192],"category.":[194],"selected":[196],"then":[199],"leveraged":[200],"initialize":[202],"detector":[205],"classification":[208],"Finally,":[212],"an":[213],"assignment":[216,233],"(AFA)":[217],"introduced":[220],"transfer":[222],"learned":[224],"domain,":[230],"category":[235],"labels":[236],"features.":[238],"asynchronously":[244],"with":[245],"assigned":[247],"mitigate":[250],"bias.":[253],"Extensive":[254],"experiments":[255],"conducted":[256],"diverse":[258],"datasets":[260],"demonstrate":[261],"that":[262],"proposed":[264],"method":[265],"consistently":[266],"outperforms":[267],"state-of-the-art":[268],"approaches,":[270],"achieving":[271],"performance":[272],"gains":[273],"1.1":[275],"5.5":[277],"mAP.":[278],"Code":[279],"available":[281],"at":[282],"https://github.com/Jandsome/CCKM.":[283]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-25T06:01:18.069262","created_date":"2026-04-21T00:00:00"}