{"id":"https://openalex.org/W4408352459","doi":"https://doi.org/10.1109/icassp49660.2025.10889554","title":"A Two-Stage AIGC Image Quality Assessment with T2I Correspondence and Visual Perception","display_name":"A Two-Stage AIGC Image Quality Assessment with T2I Correspondence and Visual Perception","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352459","doi":"https://doi.org/10.1109/icassp49660.2025.10889554"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889554","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5036611087","display_name":"Jili Xia","orcid":"https://orcid.org/0000-0001-8326-9360"},"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":true,"raw_author_name":"Jili Xia","raw_affiliation_strings":["Xidian University,School of Electronic Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Electronic Engineering,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":["Xidian University,School of Electronic Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Electronic Engineering,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748112","display_name":"Bo Hu","orcid":"https://orcid.org/0000-0001-5874-3315"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Hu","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications,Key Laboratory of Image Cognition,Chongqing,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications,Key Laboratory of Image Cognition,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101936635","display_name":"Bo Han","orcid":"https://orcid.org/0000-0001-6282-5428"},"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":"Bo Han","raw_affiliation_strings":["Xidian University,School of Electronic Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Electronic Engineering,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"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":["Xidian University,School of Electronic Engineering,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Electronic Engineering,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036611087"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.2655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.79133108,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9904000163078308,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9904000163078308,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9740999937057495,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6503095626831055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5984524488449097},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5897207260131836},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.5747998952865601},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.554002046585083},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5391073822975159},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4970763027667999},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44908684492111206},{"id":"https://openalex.org/keywords/visual-perception","display_name":"Visual perception","score":0.4354780614376068},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.21032342314720154},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07621809840202332},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.06006994843482971}],"concepts":[{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6503095626831055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5984524488449097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5897207260131836},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.5747998952865601},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.554002046585083},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5391073822975159},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4970763027667999},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44908684492111206},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.4354780614376068},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.21032342314720154},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07621809840202332},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.06006994843482971},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889554","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1592262254","https://openalex.org/W1974013408","https://openalex.org/W1979451680","https://openalex.org/W2051596736","https://openalex.org/W2148848374","https://openalex.org/W2161907179","https://openalex.org/W2194775991","https://openalex.org/W2563786098","https://openalex.org/W2676303985","https://openalex.org/W2789886397","https://openalex.org/W2891064167","https://openalex.org/W2891604443","https://openalex.org/W2905544033","https://openalex.org/W2953590133","https://openalex.org/W3002992380","https://openalex.org/W3035719652","https://openalex.org/W3135955502","https://openalex.org/W4206064403","https://openalex.org/W4287847187","https://openalex.org/W4312933868","https://openalex.org/W4382462760","https://openalex.org/W4386211581","https://openalex.org/W4387010079","https://openalex.org/W4391490252","https://openalex.org/W4402904202","https://openalex.org/W4402904322","https://openalex.org/W4402915913","https://openalex.org/W4402979192","https://openalex.org/W6637373629","https://openalex.org/W6790978476","https://openalex.org/W6791353385","https://openalex.org/W6810334672","https://openalex.org/W6860435441"],"related_works":["https://openalex.org/W1897960459","https://openalex.org/W2002567531","https://openalex.org/W180818492","https://openalex.org/W4212996970","https://openalex.org/W2033349420","https://openalex.org/W243736014","https://openalex.org/W4318185075","https://openalex.org/W2964529313","https://openalex.org/W1974005862","https://openalex.org/W2984197669"],"abstract_inverted_index":{"Image":[0],"quality":[1,37,110,146],"assessment":[2,111],"(IQA)":[3],"of":[4,38,58,71,120,125,159],"artificial":[5],"intelligence-generated":[6],"content":[7],"(AIGC)":[8],"has":[9],"recently":[10],"attracted":[11],"significant":[12],"research":[13],"attention.":[14],"Unlike":[15],"general-purpose":[16],"IQA,":[17],"which":[18],"primarily":[19],"focuses":[20],"on":[21,100,150],"evaluating":[22],"image":[23,73],"content,":[24],"AIGCIQA":[25,50],"often":[26],"requires":[27],"addressing":[28],"both":[29,114],"the":[30,35,56,59,84,97,108,123,135,145,156,160],"Text-to-Image":[31],"(T2I)":[32],"correspondence":[33,86],"and":[34,77,88,116,153],"perceptual":[36,109],"images.":[39],"To":[40],"address":[41],"this":[42,44],"requirement,":[43],"paper":[45],"proposes":[46],"a":[47,90],"novel":[48],"two-stage":[49],"method.":[51,162],"The":[52,104],"first":[53],"stage":[54,106],"evaluates":[55],"alignment":[57],"AI-generated":[60],"images":[61],"(AIGIs)":[62],"with":[63,134],"their":[64,132],"corresponding":[65],"descriptions,":[66],"serving":[67],"as":[68],"an":[69],"indicator":[70],"overall":[72,136],"quality.":[74],"Specifically,":[75],"positive":[76],"negative":[78],"prompts":[79],"are":[80,141],"constructed":[81],"to":[82,95,131],"describe":[83],"T2I":[85],"degree,":[87],"then":[89],"CLIP":[91],"model":[92],"is":[93,128],"employed":[94],"predict":[96],"degree":[98],"based":[99],"these":[101],"image-prompt":[102],"pairs.":[103],"second":[105],"refines":[107],"by":[112],"integrating":[113],"global":[115],"local":[117,126],"degradation":[118],"features":[119,127],"AIGIs.":[121],"Importantly,":[122],"contribution":[124],"measured":[129],"according":[130],"correlation":[133],"image,":[137],"ensuring":[138],"key":[139],"regions":[140],"adequately":[142],"represented":[143],"in":[144],"prediction.":[147],"Experimental":[148],"results":[149],"AGIQA-1K,":[151],"AGIQA-3K,":[152],"AIGCIQA2023":[154],"demonstrate":[155],"superior":[157],"performance":[158],"proposed":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}