{"id":"https://openalex.org/W4415708081","doi":"https://doi.org/10.1109/icme59968.2025.11209481","title":"Enhancing Open-Vocabulary Panoptic Segmentation with Semantic-Guided Q-Tuning","display_name":"Enhancing Open-Vocabulary Panoptic Segmentation with Semantic-Guided Q-Tuning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708081","doi":"https://doi.org/10.1109/icme59968.2025.11209481"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209481","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":"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/A5110299873","display_name":"Yanxiang Huang","orcid":"https://orcid.org/0009-0003-2172-0074"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yanxiang Huang","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Applied Mathematics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Applied Mathematics","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100324061","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0003-4242-0866"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Shandong University,College of Control Science and Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,College of Control Science and Engineering","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052891887","display_name":"Y. Wang","orcid":"https://orcid.org/0009-0001-6097-4881"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiang Wang","raw_affiliation_strings":["Stevens Institute of Technology,School of Business"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology,School of Business","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014198028","display_name":"Daolin Du","orcid":"https://orcid.org/0000-0003-1764-2205"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongtai Du","raw_affiliation_strings":["Carnegie Mellon University,College of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,College of Engineering","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023320063","display_name":"Yuping Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuping Yuan","raw_affiliation_strings":["DRFT,Information and Network Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DRFT,Information and Network Institute","institution_ids":["https://openalex.org/I4210108629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112126645","display_name":"Zheng Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I28813325","display_name":"Civil Aviation University of China","ror":"https://ror.org/03je71k37","country_code":"CN","type":"education","lineage":["https://openalex.org/I28813325"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhao","raw_affiliation_strings":["Civil Aviation University of China,College of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil Aviation University of China,College of Information Engineering and Automation","institution_ids":["https://openalex.org/I28813325"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8711000084877014,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8711000084877014,"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":0.027300000190734863,"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":0.019700000062584877,"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/projection","display_name":"Projection (relational algebra)","score":0.6317999958992004},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5515999794006348},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4519999921321869},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4465999901294708},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4377000033855438},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.40459999442100525},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3772999942302704},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36169999837875366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7570000290870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6912999749183655},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6317999958992004},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6245999932289124},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4519999921321869},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4377000033855438},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C138569888","wikidata":"https://www.wikidata.org/wiki/Q828310","display_name":"Panopticon","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209481","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W2125215748","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2507296351","https://openalex.org/W2561196672","https://openalex.org/W2781228439","https://openalex.org/W2963150697","https://openalex.org/W2963499153","https://openalex.org/W2999219213","https://openalex.org/W3009593063","https://openalex.org/W3034355852","https://openalex.org/W3034445502","https://openalex.org/W3138516171","https://openalex.org/W4236362309","https://openalex.org/W4312815172","https://openalex.org/W4386065512","https://openalex.org/W4386065874","https://openalex.org/W4386075561","https://openalex.org/W4386075819","https://openalex.org/W4386076397","https://openalex.org/W4390874207","https://openalex.org/W4391547487","https://openalex.org/W4399666346","https://openalex.org/W4402703011","https://openalex.org/W4402703023"],"related_works":[],"abstract_inverted_index":{"Open-vocabulary":[0],"panoptic":[1],"segmentation,":[2],"tasked":[3],"with":[4,12,98],"segmenting":[5],"images":[6],"based":[7],"on":[8],"textual":[9],"descriptions,":[10],"struggles":[11],"generalization":[13],"across":[14,122],"domains":[15],"and":[16],"efficiency":[17],"in":[18],"training.":[19],"Our":[20],"analysis":[21],"pinpoints":[22],"mask":[23,42,65,85],"classification":[24,43],"as":[25],"the":[26,74,80,89,103,111,134],"primary":[27],"bottleneck.":[28],"To":[29],"this":[30],"end,":[31],"we":[32],"propose":[33],"Semantic":[34],"Guided":[35],"Q-Tuning":[36],"(SGQT),":[37],"a":[38,50],"framework":[39],"that":[40],"bolsters":[41],"via":[44],"two":[45],"innovations.":[46],"First,":[47],"SGQT":[48,117],"leverages":[49],"multimodal":[51],"Semantic-guided":[52],"Mask":[53],"Attention":[54],"mechanism":[55],"to":[56,73,91,94,133],"infuse":[57],"task-awareness":[58],"into":[59],"regional":[60],"information":[61],"extraction,":[62],"thereby":[63],"enhancing":[64],"classification.":[66,86],"Second,":[67],"it":[68],"introduces":[69],"Query":[70],"Projection":[71],"Tuning":[72],"Vision":[75],"Language":[76],"Model":[77],"(VLM),":[78],"fine-tuning":[79],"query":[81],"projection":[82],"layers":[83],"for":[84],"This":[87],"enables":[88],"model":[90],"swiftly":[92],"adapt":[93],"new":[95,119],"image":[96],"distributions":[97],"minimal":[99],"additional":[100],"training,":[101],"preserving":[102],"VLM\u2019s":[104],"pre-trained":[105],"knowledge.":[106],"Extensive":[107],"ablation":[108],"studies":[109],"confirm":[110],"superiority":[112],"of":[113],"our":[114],"approach.":[115],"Notably,":[116],"sets":[118],"state-of-the-art":[120],"results":[121],"representative":[123],"benchmarks,":[124],"while":[125],"reducing":[126],"training":[127],"costs":[128],"by":[129],"nearly":[130],"10\u00d7":[131],"compared":[132],"previous":[135],"best":[136],"method.":[137]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-30T00:00:00"}