{"id":"https://openalex.org/W4415708209","doi":"https://doi.org/10.1109/icme59968.2025.11209279","title":"OpenDUN: To Discover Unknown Number of Visual Categories","display_name":"OpenDUN: To Discover Unknown Number of Visual Categories","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708209","doi":"https://doi.org/10.1109/icme59968.2025.11209279"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209279","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209279","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5038337519","display_name":"Shih-Chieh Wu","orcid":"https://orcid.org/0009-0004-0066-5253"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sik Chit Wu","raw_affiliation_strings":["Peking University,School of Electronic and Computer Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058644424","display_name":"Munan Ning","orcid":"https://orcid.org/0009-0005-3418-085X"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Munan Ning","raw_affiliation_strings":["Peking University, Pengcheng Lab,School of Electronic and Computer Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Peking University, Pengcheng Lab,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391498","display_name":"Wei Dong","orcid":"https://orcid.org/0000-0002-7299-7693"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wei","raw_affiliation_strings":["Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051649145","display_name":"Yefeng Zheng","orcid":"https://orcid.org/0000-0003-2195-2847"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yefeng Zheng","raw_affiliation_strings":["Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014222179","display_name":"Donghuan Lu","orcid":"https://orcid.org/0000-0002-8399-7410"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghuan Lu","raw_affiliation_strings":["Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tencent YouTu Lab,Jarvis Research Center,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5116493713","display_name":"Li Yuan","orcid":"https://orcid.org/0000-0002-2120-5588"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yuan","raw_affiliation_strings":["Peking University, Pengcheng Lab,School of Electronic and Computer Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Peking University, Pengcheng Lab,School of Electronic and Computer Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5038337519"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17519738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.545799970626831,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.545799970626831,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.1534000039100647,"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":0.04170000180602074,"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/categorical-variable","display_name":"Categorical variable","score":0.7296000123023987},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6018000245094299},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5694000124931335},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5135999917984009},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36910000443458557},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.34290000796318054},{"id":"https://openalex.org/keywords/division","display_name":"Division (mathematics)","score":0.336899995803833}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.7296000123023987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6385999917984009},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6018000245094299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5835000276565552},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5694000124931335},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5135999917984009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4731000065803528},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32339999079704285},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3093000054359436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3009999990463257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209279","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209279","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2051224630","https://openalex.org/W2085487226","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2222512263","https://openalex.org/W2787720882","https://openalex.org/W2904427185","https://openalex.org/W2963149653","https://openalex.org/W2963446712","https://openalex.org/W2963875483","https://openalex.org/W2990604239","https://openalex.org/W3035081753","https://openalex.org/W4312281441","https://openalex.org/W4375839990"],"related_works":[],"abstract_inverted_index":{"Open-Set":[0],"methods":[1],"have":[2],"relaxed":[3],"the":[4,17,24,57,75,84,97,104,111,127,143,146,151,154,159],"underlying":[5],"assumption":[6],"made":[7],"by":[8,27],"most":[9,40],"image":[10],"recognition":[11],"studies":[12],"that":[13,126],"all":[14],"samples":[15,86],"in":[16,36,59,149],"test":[18],"and":[19,109,158],"training":[20,37],"datasets":[21,138],"belong":[22],"to":[23,95,141],"same":[25],"classes":[26,33,79,108],"considering":[28],"only":[29],"a":[30,45,68,119],"part":[31],"of":[32,41,50,77,90,106,114,145,153,161],"are":[34,139],"known":[35,46],"dataset.":[38],"However,":[39],"these":[42],"approaches":[43],"require":[44],"or":[47],"predefined":[48],"number":[49,76,105,157],"novel":[51,78,107,155],"classes,":[52],"which":[53],"is":[54,80,123],"often":[55],"not":[56],"case":[58],"real":[60],"applications.":[61],"In":[62,117],"this":[63],"study,":[64],"we":[65],"aim":[66],"at":[67],"more":[69],"difficult":[70],"but":[71],"practical":[72],"scenario,":[73],"where":[74],"unknown.":[81],"By":[82],"merging":[83,129],"unlabeled":[85,115,162],"into":[87],"clusters":[88],"instead":[89],"directly":[91],"assigning":[92],"categorical":[93],"labels":[94],"them,":[96],"proposed":[98,147],"end-to-end":[99],"framework":[100],"can":[101,130],"simultaneously":[102],"estimate":[103],"learn":[110],"appropriate":[112],"division":[113],"samples.":[116,163],"addition,":[118],"cluster":[120],"scattering":[121],"strategy":[122],"introduced":[124],"such":[125],"erroneous":[128],"be":[131],"alleviated.":[132],"Comprehensive":[133],"experiments":[134],"on":[135],"three":[136],"benchmark":[137],"conducted":[140],"demonstrate":[142],"superiority":[144],"method":[148],"both":[150],"estimation":[152],"class":[156],"classification":[160]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}