{"id":"https://openalex.org/W4414359815","doi":"https://doi.org/10.24963/ijcai.2025/473","title":"kgMBQA: Quality Knowledge Graph-driven Multimodal Blind Image Assessment","display_name":"kgMBQA: Quality Knowledge Graph-driven Multimodal Blind Image Assessment","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359815","doi":"https://doi.org/10.24963/ijcai.2025/473"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/473","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5088113891","display_name":"Wuyuan Xie","orcid":"https://orcid.org/0000-0001-5791-8267"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wuyuan Xie","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tingcheng Bian","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingcheng Bian","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080596209","display_name":"Miaohui Wang","orcid":"https://orcid.org/0000-0003-1125-9299"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miaohui Wang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.5628,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71279695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4245","last_page":"4253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9761000275611877,"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/credibility","display_name":"Credibility","score":0.7696999907493591},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6291999816894531},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.6165000200271606},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5922999978065491},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5455999970436096},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44920000433921814},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4140999913215637},{"id":"https://openalex.org/keywords/explanatory-model","display_name":"Explanatory model","score":0.39590001106262207}],"concepts":[{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.7696999907493591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6825000047683716},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6291999816894531},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.6165000200271606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6014999747276306},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5922999978065491},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5455999970436096},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40540000796318054},{"id":"https://openalex.org/C2778638050","wikidata":"https://www.wikidata.org/wiki/Q5421252","display_name":"Explanatory model","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38119998574256897},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3154999911785126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/473","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Blind":[0],"image":[1,9,72,94],"assessment":[2],"aims":[3],"to":[4,39,80,121],"simulate":[5],"human":[6],"prediction":[7,50],"of":[8,48],"quality":[10,15,20,60,73,106],"distortion":[11,31],"levels":[12],"and":[13,30,33,76,90,132],"provide":[14,40],"scores.":[16],"However,":[17],"existing":[18],"unimodal":[19],"indicators":[21],"have":[22],"limited":[23],"representational":[24],"ability":[25],"when":[26],"facing":[27],"complex":[28],"contents":[29],"types,":[32],"the":[34,46,93,98,117,126],"predicted":[35],"scores":[36],"also":[37,102],"fail":[38],"explanatory":[41,63,82,107],"reasons,":[42],"which":[43],"further":[44,88],"affects":[45],"credibility":[47],"their":[49],"results.":[51],"To":[52],"address":[53],"these":[54],"challenges,":[55],"we":[56,69],"propose":[57],"a":[58],"multimodal":[59],"indicator":[61],"with":[62,92],"text":[64,85],"descriptions,":[65],"called":[66],"kgMBQA.":[67],"Specifically,":[68],"construct":[70],"an":[71],"knowledge":[74],"graph":[75],"conduct":[77],"in-depth":[78],"mining":[79],"generate":[81],"texts.":[83],"The":[84,109],"modality":[86],"is":[87],"aligned":[89],"fused":[91],"modality,":[95],"thereby":[96],"improving":[97],"model":[99],"performance":[100,119],"while":[101],"outputting":[103],"its":[104],"corresponding":[105],"description.":[108],"experimental":[110],"results":[111],"demonstrate":[112],"that":[113],"our":[114],"kgMBQA":[115],"achieves":[116],"best":[118],"compared":[120],"recent":[122],"representative":[123],"methods":[124],"on":[125],"KonIQ-10k,":[127],"LIVE":[128],"Challenge,":[129],"BIQ2021,":[130],"TID2013,":[131],"AIGC-3K":[133],"datasets.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
