{"id":"https://openalex.org/W4417168941","doi":"https://doi.org/10.1109/tip.2025.3639984","title":"AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similarity","display_name":"AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similarity","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4417168941","doi":"https://doi.org/10.1109/tip.2025.3639984","pmid":"https://pubmed.ncbi.nlm.nih.gov/41364576"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2025.3639984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3639984","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/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":["School of Electronic Engineering, Xidian University, Xi’an, China"],"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"],"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/A5015874725","display_name":"Cheng Deng","orcid":"https://orcid.org/0000-0003-2620-3247"},"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":"Cheng Deng","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"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/A5033615240","display_name":"Leida Li","orcid":"https://orcid.org/0000-0001-9069-8796"},"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":"Leida Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101313930","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"],"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":5,"corresponding_author_ids":["https://openalex.org/A5036611087"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.2181,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85700937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"34","issue":null,"first_page":"8216","last_page":"8228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9854000210762024,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9854000210762024,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.006000000052154064,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0015999999595806003,"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/similarity","display_name":"Similarity (geometry)","score":0.7504000067710876},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6209999918937683},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.567300021648407},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5651999711990356},{"id":"https://openalex.org/keywords/quality-score","display_name":"Quality Score","score":0.4672999978065491},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4408000111579895},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41370001435279846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742000222206116},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7504000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6978999972343445},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6209999918937683},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.567300021648407},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5651999711990356},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.4672999978065491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.41130000352859497},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39419999718666077},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C139489369","wikidata":"https://www.wikidata.org/wiki/Q770846","display_name":"Structural similarity","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.2888999879360199},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2847999930381775}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2025.3639984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3639984","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:41364576","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41364576","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":92,"referenced_works":["https://openalex.org/W1916445035","https://openalex.org/W1977725648","https://openalex.org/W1982471090","https://openalex.org/W2051596736","https://openalex.org/W2092377492","https://openalex.org/W2148848374","https://openalex.org/W2161907179","https://openalex.org/W2162692770","https://openalex.org/W2171349048","https://openalex.org/W2194775991","https://openalex.org/W2473697052","https://openalex.org/W2563786098","https://openalex.org/W2620678416","https://openalex.org/W2765934933","https://openalex.org/W2897228451","https://openalex.org/W2905544033","https://openalex.org/W2953590133","https://openalex.org/W2963966654","https://openalex.org/W2963975576","https://openalex.org/W2964024144","https://openalex.org/W3002992380","https://openalex.org/W3015686580","https://openalex.org/W3034882073","https://openalex.org/W3035359990","https://openalex.org/W3035595647","https://openalex.org/W3035712445","https://openalex.org/W3035719652","https://openalex.org/W3036239693","https://openalex.org/W3126164993","https://openalex.org/W3130885914","https://openalex.org/W3135955502","https://openalex.org/W3153355178","https://openalex.org/W3159198982","https://openalex.org/W3176622443","https://openalex.org/W3193135654","https://openalex.org/W3194280054","https://openalex.org/W3194293177","https://openalex.org/W3204198763","https://openalex.org/W3205717164","https://openalex.org/W3205725084","https://openalex.org/W3210514413","https://openalex.org/W4206064403","https://openalex.org/W4213430676","https://openalex.org/W4214745154","https://openalex.org/W4224267514","https://openalex.org/W4281485015","https://openalex.org/W4285204090","https://openalex.org/W4287847187","https://openalex.org/W4304092064","https://openalex.org/W4312327698","https://openalex.org/W4312563428","https://openalex.org/W4312910992","https://openalex.org/W4312956471","https://openalex.org/W4312980231","https://openalex.org/W4319663695","https://openalex.org/W4367146870","https://openalex.org/W4382462760","https://openalex.org/W4385695917","https://openalex.org/W4386071753","https://openalex.org/W4386076169","https://openalex.org/W4386076425","https://openalex.org/W4386211581","https://openalex.org/W4387010079","https://openalex.org/W4387757549","https://openalex.org/W4389610036","https://openalex.org/W4390873054","https://openalex.org/W4390874002","https://openalex.org/W4391490252","https://openalex.org/W4391697001","https://openalex.org/W4392172801","https://openalex.org/W4392667279","https://openalex.org/W4394593151","https://openalex.org/W4394770386","https://openalex.org/W4396667876","https://openalex.org/W4396680484","https://openalex.org/W4396818947","https://openalex.org/W4400070365","https://openalex.org/W4401567558","https://openalex.org/W4402704606","https://openalex.org/W4402753956","https://openalex.org/W4402904202","https://openalex.org/W4402904322","https://openalex.org/W4402915913","https://openalex.org/W4402916204","https://openalex.org/W4402916469","https://openalex.org/W4402979192","https://openalex.org/W4404536559","https://openalex.org/W4404613040","https://openalex.org/W4404840339","https://openalex.org/W4405778885","https://openalex.org/W4406039053","https://openalex.org/W4413145151"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"AI-generated":[1],"images":[2,23],"(AIGIs),":[3],"synthesized":[4],"based":[5,59],"on":[6,60,208],"initial":[7,62,186],"textual":[8,56],"prompts,":[9],"have":[10],"attracted":[11],"widespread":[12],"attention.":[13],"However,":[14,84],"due":[15],"to":[16,102,107,148,154,171,188],"limitations":[17],"in":[18],"current":[19],"generation":[20],"techniques,":[21],"these":[22,113,195],"often":[24],"exhibit":[25],"degraded":[26],"perceptual":[27,39,66,93,140],"quality":[28,40,69,96,120,143,151,174,204,212],"and":[29,41,67,71,80,94,98,129,141,168,176,184,202,217],"semantic":[30,104,190],"misalignment":[31],"with":[32],"the":[33,48,61,77,81,89,92,146,161,165,177,181,185,215,220],"guiding":[34],"prompts.":[35],"Therefore,":[36],"evaluating":[37],"both":[38,65],"text-to-image":[42],"alignment":[43,68,95,142],"is":[44],"essential":[45],"for":[46,64,139],"optimizing":[47],"performance":[49],"of":[50,219],"generative":[51],"models.":[52],"Existing":[53],"methods":[54],"design":[55],"prompts":[57,87,138,170],"solely":[58],"prompt":[63,79,128,135,187],"tasks,":[70,97],"compute":[72],"only":[73],"coarse-grained":[74],"similarity":[75,100,131,159,163,179],"between":[76,91,164,180],"designed":[78],"generated":[82,166,182],"image.":[83],"such":[85],"task-agnostic":[86],"overlook":[88],"distinctions":[90],"coarse-level":[99,162],"fails":[101],"capture":[103,149,172],"details,":[105],"leading":[106],"suboptimal":[108],"evaluation":[109,156],"performance.":[110],"To":[111],"address":[112],"challenges,":[114],"we":[115],"propose":[116],"a":[117],"novel":[118],"AIGI":[119,211],"assessment":[121],"framework,":[122],"termed":[123],"TPMS,":[124],"which":[125],"incorporates":[126],"task-specific":[127,134,169],"multi-granularity":[130],"computation.":[132],"The":[133],"constructs":[136],"dedicated":[137],"respectively,":[144],"allowing":[145],"model":[147],"distinct":[150],"cues":[152],"tailored":[153],"each":[155],"task.":[157],"Multi-granularity":[158],"measures":[160],"image":[167,183],"global":[173],"characteristics,":[175],"fine-level":[178],"enhance":[189],"detail":[191],"awareness.":[192],"By":[193],"integrating":[194],"two":[196],"complementary":[197],"similarities,":[198],"TPMS":[199],"enables":[200],"precise":[201],"robust":[203],"prediction.":[205],"Extensive":[206],"experiments":[207],"four":[209],"widely-used":[210],"benchmarks":[213],"validate":[214],"effectiveness":[216],"superiority":[218],"proposed":[221],"framework.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-12-09T00:00:00"}