{"id":"https://openalex.org/W3204198763","doi":"https://doi.org/10.1109/tmm.2021.3114551","title":"A Novel Rank Learning Based No-Reference Image Quality Assessment Method","display_name":"A Novel Rank Learning Based No-Reference Image Quality Assessment Method","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W3204198763","doi":"https://doi.org/10.1109/tmm.2021.3114551","mag":"3204198763"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2021.3114551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3114551","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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/A5023617834","display_name":"Fu-Zhao Ou","orcid":"https://orcid.org/0000-0003-1245-8345"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fu-Zhao Ou","raw_affiliation_strings":["School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064709384","display_name":"Yuan\u2010Gen Wang","orcid":"https://orcid.org/0000-0003-3010-4196"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan-Gen Wang","raw_affiliation_strings":["School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364819","display_name":"Jin Li","orcid":"https://orcid.org/0000-0003-0385-8793"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Li","raw_affiliation_strings":["Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091556887","display_name":"Guopu Zhu","orcid":"https://orcid.org/0000-0001-7956-5343"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guopu Zhu","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023617834"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":3.0,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.92878011,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"24","issue":null,"first_page":"4197","last_page":"4211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9987000226974487,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9927999973297119,"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/computer-science","display_name":"Computer science","score":0.79740971326828},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.7568431496620178},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6649560332298279},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6433308124542236},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6368913650512695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6352230906486511},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5845792293548584},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5731136202812195},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5616630911827087},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5407237410545349},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.51971036195755},{"id":"https://openalex.org/keywords/quality-score","display_name":"Quality Score","score":0.4621729254722595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4443448483943939},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4339365065097809},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4033352732658386},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.2561550736427307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12380969524383545}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79740971326828},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.7568431496620178},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6649560332298279},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6433308124542236},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6368913650512695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6352230906486511},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5845792293548584},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5731136202812195},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5616630911827087},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5407237410545349},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.51971036195755},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.4621729254722595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4443448483943939},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4339365065097809},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4033352732658386},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2561550736427307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12380969524383545},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2021.3114551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3114551","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G7706713251","display_name":null,"funder_award_id":"61872099","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7809598670","display_name":null,"funder_award_id":"61872350","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W56385144","https://openalex.org/W1686810756","https://openalex.org/W1974013408","https://openalex.org/W1977246677","https://openalex.org/W1982471090","https://openalex.org/W1984514441","https://openalex.org/W1987489060","https://openalex.org/W2051596736","https://openalex.org/W2052287864","https://openalex.org/W2059283460","https://openalex.org/W2063360098","https://openalex.org/W2095650263","https://openalex.org/W2126902946","https://openalex.org/W2129644086","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2148848374","https://openalex.org/W2149007912","https://openalex.org/W2155893237","https://openalex.org/W2161907179","https://openalex.org/W2162692770","https://openalex.org/W2171349048","https://openalex.org/W2286686646","https://openalex.org/W2417288846","https://openalex.org/W2463833054","https://openalex.org/W2473697052","https://openalex.org/W2527269634","https://openalex.org/W2546855109","https://openalex.org/W2556068545","https://openalex.org/W2563786098","https://openalex.org/W2566149141","https://openalex.org/W2611915171","https://openalex.org/W2615207113","https://openalex.org/W2737134362","https://openalex.org/W2754213847","https://openalex.org/W2761499647","https://openalex.org/W2767836774","https://openalex.org/W2807793257","https://openalex.org/W2891645170","https://openalex.org/W2897228451","https://openalex.org/W2901266255","https://openalex.org/W2903193781","https://openalex.org/W2904166318","https://openalex.org/W2905544033","https://openalex.org/W2914658805","https://openalex.org/W2914913933","https://openalex.org/W2953590133","https://openalex.org/W2963596827","https://openalex.org/W2963975576","https://openalex.org/W2964065910","https://openalex.org/W2970435399","https://openalex.org/W3002992380","https://openalex.org/W3006233221","https://openalex.org/W3030380536","https://openalex.org/W3035595647","https://openalex.org/W3035719652","https://openalex.org/W3090767700","https://openalex.org/W3091249416","https://openalex.org/W3100404621","https://openalex.org/W3102733987","https://openalex.org/W3102939503","https://openalex.org/W3103635814","https://openalex.org/W3135479537","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W4387073571","https://openalex.org/W3194862240","https://openalex.org/W2526960468","https://openalex.org/W4206325381","https://openalex.org/W2295706819","https://openalex.org/W2161907179","https://openalex.org/W2043597472","https://openalex.org/W54224318","https://openalex.org/W2552902349","https://openalex.org/W4226186675"],"abstract_inverted_index":{"Recently,":[0],"applying":[1],"deep":[2],"learning":[3,31,49,93],"to":[4,26,59,137,183,198,205,219],"no-reference":[5],"image":[6,146],"quality":[7,155],"assessment":[8],"(NR-IQA)":[9],"has":[10,23],"received":[11],"significant":[12],"attention.":[13],"Especially":[14],"in":[15,80,103,115],"the":[16,27,37,54,60,67,70,117,127,139,144,189,216,221,230,238,241,255],"last":[17],"five":[18],"years,":[19],"an":[20,112,124,170,180],"increasing":[21],"interest":[22],"been":[24],"drawn":[25],"studies":[28],"of":[29,39,62,72,126,175,215,240],"rank":[30,48,64,74,92,145,176,185,191],"since":[32],"it":[33],"can":[34,251],"help":[35],"mitigate":[36],"problem":[38],"small":[40],"IQA":[41,101,217,231],"datasets.":[42],"However,":[43],"on":[44,229],"one":[45],"hand,":[46,69],"existing":[47,73],"is":[50,77,121],"not":[51],"suitable":[52],"for":[53],"authentically":[55],"distorted":[56],"images":[57],"due":[58],"lack":[61],"generated":[63,190],"samples.":[65,147],"On":[66],"other":[68],"output":[71],"loss":[75,166],"functions":[76],"uncontrollable,":[78],"resulting":[79],"reduced":[81],"performance.":[82],"Motivated":[83],"by":[84,168],"these":[85],"two":[86],"limitations,":[87],"we":[88,109,159,212],"propose":[89],"a":[90,161,200,207],"novel":[91],"based":[94],"NR-IQA":[95],"method,":[96],"termed":[97],"controllable":[98,162],"list-wise":[99,163],"ranking":[100,156,164],"(CLRIQA)":[102],"this":[104],"paper.":[105],"To":[106],"be":[107,252],"specific,":[108],"first":[110],"present":[111],"imaging-heuristic":[113],"approach,":[114],"which":[116],"over-":[118],"and":[119,130,133,142,172,178,193,234,248],"under-exposure":[120],"formulated":[122],"as":[123],"inverse":[125],"Weber-Fechner":[128],"law,":[129],"fusion":[131],"strategy":[132],"compression":[134],"are":[135,150,196,227],"adopted,":[136],"simulate":[138],"authentic":[140],"distortion":[141],"generate":[143],"These":[148],"samples":[149,192],"label-free":[151],"yet":[152],"associated":[153],"with":[154],"information.":[157],"Then":[158],"design":[160],"(CLR)":[165],"function":[167],"setting":[169],"upper":[171],"lower":[173],"bound":[174],"range":[177],"introducing":[179],"adaptive":[181],"margin":[182],"tune":[184],"interval.":[186],"Finally,":[187],"both":[188],"proposed":[194,242],"CLR":[195],"used":[197],"pre-train":[199],"convolutional":[201],"neural":[202],"network.":[203],"Moreover,":[204],"obtain":[206],"more":[208],"accurate":[209],"prediction":[210],"model,":[211],"take":[213],"advantage":[214],"datasets":[218],"fine-tune":[220],"pre-trained":[222],"network":[223,249],"further.":[224],"Various":[225],"experiments":[226],"conducted":[228],"benchmark":[232],"datasets,":[233],"experimental":[235],"results":[236],"demonstrate":[237],"effectiveness":[239],"CLRIQA":[243],"method.":[244],"The":[245],"source":[246],"code":[247],"model":[250],"downloaded":[253],"at":[254],"following":[256],"web":[257],"address:":[258],"<italic":[259],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[260],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><uri>https://github.com</uri>":[261],"<inline-formula><tex-math":[262,265],"notation=\"LaTeX\">$/$</tex-math></inline-formula>":[263,266],"GZHU-DVL":[264],"CLRIQA</i>":[267],".":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
