{"id":"https://openalex.org/W7134850890","doi":"https://doi.org/10.1109/lsp.2026.3672387","title":"Degradation-Aware Contrastive Learning for Blind Image Quality Assessment","display_name":"Degradation-Aware Contrastive Learning for Blind Image Quality Assessment","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7134850890","doi":"https://doi.org/10.1109/lsp.2026.3672387"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3672387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3672387","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5120913992","display_name":"Xiaodong Bi","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Bi","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128666654","display_name":"Xiaohai He","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohai He","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-8399-3172","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102700041","display_name":"Shuhua Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhua Xiong","raw_affiliation_strings":["College of Electronics and Information Engineering, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423697","display_name":"Zheng Liu","orcid":"https://orcid.org/0000-0002-7241-3483"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Liu","raw_affiliation_strings":["National Innovation Center for UHD Video Technology, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Innovation Center for UHD Video Technology, Chengdu, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017016905","display_name":"Ray E. Sheriff","orcid":"https://orcid.org/0000-0003-4143-692X"},"institutions":[{"id":"https://openalex.org/I165525304","display_name":"Edge Hill University","ror":"https://ror.org/028ndzd53","country_code":"GB","type":"education","lineage":["https://openalex.org/I165525304"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Raymond Edward Sheriff","raw_affiliation_strings":["Department of Computer Science, Edge Hill University, Ormskirk, U.K"],"raw_orcid":"https://orcid.org/0000-0003-4143-692X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Edge Hill University, Ormskirk, U.K","institution_ids":["https://openalex.org/I165525304"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29753987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1220","last_page":"1224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9204999804496765,"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":0.9204999804496765,"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":0.016899999231100082,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.014800000004470348,"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/generalization","display_name":"Generalization","score":0.6883999705314636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5794000029563904},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5449000000953674},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5263000130653381},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.487199991941452},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.46470001339912415},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4629000127315521},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4487000107765198},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4413999915122986},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.430400013923645}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7631999850273132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705299973487854},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6883999705314636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5794000029563904},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5449000000953674},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5263000130653381},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.487199991941452},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.3961000144481659},{"id":"https://openalex.org/C197654239","wikidata":"https://www.wikidata.org/wiki/Q7430757","display_name":"Scene statistics","level":3,"score":0.39430001378059387},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.37229999899864197},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3538999855518341},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.2924000024795532},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3672387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3672387","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.764004111289978,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3824735718","display_name":null,"funder_award_id":"62211530110","funder_id":"https://openalex.org/F4320327720","funder_display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China"},{"id":"https://openalex.org/G8650837712","display_name":null,"funder_award_id":"62271336","funder_id":"https://openalex.org/F4320327720","funder_display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320327720","display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1974013408","https://openalex.org/W1979451680","https://openalex.org/W1982471090","https://openalex.org/W2148848374","https://openalex.org/W2161907179","https://openalex.org/W2171349048","https://openalex.org/W2473697052","https://openalex.org/W2768340063","https://openalex.org/W2888928533","https://openalex.org/W2905544033","https://openalex.org/W2953590133","https://openalex.org/W2985068832","https://openalex.org/W3002992380","https://openalex.org/W3109622386","https://openalex.org/W3134397751","https://openalex.org/W3167995751","https://openalex.org/W3174722860","https://openalex.org/W3194787802","https://openalex.org/W3210514413","https://openalex.org/W4210361933","https://openalex.org/W4210632776","https://openalex.org/W4214745154","https://openalex.org/W4319300354","https://openalex.org/W4319336354","https://openalex.org/W4366308799","https://openalex.org/W4376849840","https://openalex.org/W4385339047","https://openalex.org/W4386071753","https://openalex.org/W4390739099","https://openalex.org/W4394625665","https://openalex.org/W4396680484","https://openalex.org/W4402039157","https://openalex.org/W4403181996","https://openalex.org/W4403390109","https://openalex.org/W4403462839","https://openalex.org/W4406172208","https://openalex.org/W4406610296","https://openalex.org/W4408186605","https://openalex.org/W4409326472"],"related_works":[],"abstract_inverted_index":{"Images":[0],"affected":[1],"by":[2,21,95],"the":[3,77,86,104],"same":[4],"distortion":[5],"type":[6],"and":[7,74,118],"level":[8],"usually":[9],"have":[10],"consistent":[11],"statistical":[12],"characteristics,":[13],"while":[14],"different":[15],"distortions":[16],"exhibit":[17],"significant":[18],"discriminability.":[19],"Inspired":[20],"this":[22,24],"observation,":[23],"paper":[25],"proposes":[26],"a":[27,45,71,96],"Degradation-aware":[28],"Contrast":[29],"Learning":[30],"(DCL)":[31],"framework":[32],"to":[33,56,80,91],"explicitly":[34],"model":[35,73],"degradation":[36,59,78],"properties":[37],"for":[38],"Blind":[39],"Image":[40],"Quality":[41],"Assessment":[42],"(BIQA).":[43],"First,":[44],"Latent":[46],"Degradation":[47],"Space":[48],"(LDS)":[49],"is":[50],"constructed":[51],"via":[52],"self-supervised":[53],"contrastive":[54],"learning":[55],"effectively":[57],"capture":[58],"features":[60,67,79,88],"from":[61],"distorted":[62],"images.":[63],"Then,":[64],"deep":[65],"semantic":[66],"are":[68,89],"extracted":[69],"using":[70],"pre-trained":[72],"fused":[75,87],"with":[76],"provide":[81],"complementary":[82],"bias":[83],"information.":[84],"Finally,":[85],"mapped":[90],"perceptual":[92],"quality":[93],"scores":[94],"regression":[97],"model.":[98],"The":[99],"experimental":[100],"results":[101],"show":[102],"that":[103],"proposed":[105],"method":[106],"outperforms":[107],"existing":[108],"state-of-the-art":[109],"BIQA":[110],"methods":[111],"in":[112],"terms":[113],"of":[114],"prediction":[115],"accuracy,":[116],"robustness,":[117],"generalization":[119],"ability.":[120]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-03-11T00:00:00"}