{"id":"https://openalex.org/W4287847187","doi":"https://doi.org/10.1109/bmsb55706.2022.9828590","title":"Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion Strategy","display_name":"Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion Strategy","publication_year":2022,"publication_date":"2022-06-15","ids":{"openalex":"https://openalex.org/W4287847187","doi":"https://doi.org/10.1109/bmsb55706.2022.9828590"},"language":"en","primary_location":{"id":"doi:10.1109/bmsb55706.2022.9828590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb55706.2022.9828590","pdf_url":null,"source":{"id":"https://openalex.org/S4363606279","display_name":"2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","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/A5044700284","display_name":"Wei Sun","orcid":"https://orcid.org/0000-0001-8162-1949"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Sun","raw_affiliation_strings":["Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015291775","display_name":"Huiyu Duan","orcid":"https://orcid.org/0000-0002-6519-4067"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyu Duan","raw_affiliation_strings":["Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043405654","display_name":"Xiongkuo Min","orcid":"https://orcid.org/0000-0001-5693-0416"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiongkuo Min","raw_affiliation_strings":["Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379203","display_name":"Li Chen","orcid":"https://orcid.org/0000-0001-9899-2535"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Chen","raw_affiliation_strings":["Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064168853","display_name":"Guangtao Zhai","orcid":"https://orcid.org/0000-0001-8165-9322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangtao Zhai","raw_affiliation_strings":["Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"06"},"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":0.9980999827384949,"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":0.8278027772903442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495898962020874},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.633446991443634},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6324836611747742},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.6064995527267456},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5498287677764893},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5472878217697144},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5393732190132141},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4671480059623718},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4306921064853668},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42785656452178955},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4107498228549957},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.395975798368454},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3564567565917969},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31474846601486206}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8278027772903442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495898962020874},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.633446991443634},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6324836611747742},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.6064995527267456},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5498287677764893},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5472878217697144},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5393732190132141},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4671480059623718},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4306921064853668},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42785656452178955},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4107498228549957},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.395975798368454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3564567565917969},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31474846601486206},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/bmsb55706.2022.9828590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb55706.2022.9828590","pdf_url":null,"source":{"id":"https://openalex.org/S4363606279","display_name":"2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G4458402607","display_name":null,"funder_award_id":"61901260,61831015","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":37,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1979451680","https://openalex.org/W1982471090","https://openalex.org/W2051596736","https://openalex.org/W2063360098","https://openalex.org/W2097117768","https://openalex.org/W2102166818","https://openalex.org/W2129644086","https://openalex.org/W2148848374","https://openalex.org/W2194775991","https://openalex.org/W2290180618","https://openalex.org/W2412782625","https://openalex.org/W2549139847","https://openalex.org/W2563786098","https://openalex.org/W2585702364","https://openalex.org/W2586275201","https://openalex.org/W2794680924","https://openalex.org/W2897228451","https://openalex.org/W2905544033","https://openalex.org/W2927842406","https://openalex.org/W2953106684","https://openalex.org/W2963163009","https://openalex.org/W2990391914","https://openalex.org/W3002992380","https://openalex.org/W3035595647","https://openalex.org/W3035712445","https://openalex.org/W3035719652","https://openalex.org/W3091249416","https://openalex.org/W3100404621","https://openalex.org/W4297665946","https://openalex.org/W4301142835","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6775845032"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W2358318464","https://openalex.org/W2964954556","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Image":[0],"quality":[1,21,29,61],"assessment":[2,30],"(IQA)":[3],"is":[4,164],"very":[5],"important":[6],"for":[7,35,79,134],"both":[8,65],"end-users":[9],"and":[10,69,130,166],"service-providers":[11],"since":[12],"a":[13,96,157],"high-quality":[14],"image":[15,28],"can":[16,167],"significantly":[17],"improve":[18],"the":[19,88,102,108,111,117,135,143,161,176],"user's":[20],"of":[22,107,123,179],"experience":[23],"(QoE).":[24],"Most":[25],"existing":[26],"blind":[27],"(BIQA)":[31],"models":[32,150,173],"were":[33],"developed":[34],"synthetically":[36],"distorted":[37],"images,":[38,45],"however,":[39],"they":[40],"perform":[41],"poorly":[42],"on":[43,151],"in-the-wild":[44,80,136,153],"which":[46,115],"are":[47,131],"widely":[48],"existed":[49],"in":[50],"various":[51,177],"practical":[52,180],"applications.":[53,181],"In":[54],"this":[55],"paper,":[56],"inspired":[57],"by":[58,64,82,156],"perceptual":[59],"visual":[60,67,124],"being":[62],"affected":[63],"low-level":[66,127],"features":[68,85,103],"high-level":[70,129],"semantic":[71],"information,":[72],"we":[73,94],"propose":[74,95],"an":[75],"effective":[76],"BIQA":[77,149],"model":[78,118,145,163],"images":[81],"considering":[83],"rich":[84],"extracted":[86],"from":[87,104,126],"convolution":[89],"neural":[90],"network":[91],"(CNN).":[92],"Specifically,":[93],"staircase":[97],"structure":[98],"to":[99,119,128,174],"hierarchically":[100],"integrate":[101],"intermediate":[105],"layers":[106],"CNN":[109,172],"into":[110],"quality-aware":[112],"feature":[113],"representation,":[114],"enables":[116],"make":[120],"full":[121],"use":[122],"information":[125],"more":[132],"suitable":[133],"IQA":[137,154],"task.":[138],"Experimental":[139],"results":[140],"show":[141],"that":[142],"proposed":[144,162],"outperforms":[146],"other":[147],"state-of-the-art":[148],"six":[152],"databases":[155],"large":[158],"margin.":[159],"Moreover,":[160],"flexible":[165],"be":[168],"replaced":[169],"with":[170],"popular":[171],"meet":[175],"needs":[178]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}