{"id":"https://openalex.org/W4389474417","doi":"https://doi.org/10.1109/mmsp59012.2023.10337664","title":"Adaptive Patch Labeling and Multi-Label Feature Selection for 360-Degree Image Quality Assessment","display_name":"Adaptive Patch Labeling and Multi-Label Feature Selection for 360-Degree Image Quality Assessment","publication_year":2023,"publication_date":"2023-09-27","ids":{"openalex":"https://openalex.org/W4389474417","doi":"https://doi.org/10.1109/mmsp59012.2023.10337664"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp59012.2023.10337664","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mmsp59012.2023.10337664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04729225/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036140037","display_name":"Abderrezzaq Sendjasni","orcid":"https://orcid.org/0000-0002-6533-5675"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Abderrezzaq Sendjasni","raw_affiliation_strings":["CNRS, Univ. Poitiers,XLIM, UMR 7252,France"],"affiliations":[{"raw_affiliation_string":"CNRS, Univ. Poitiers,XLIM, UMR 7252,France","institution_ids":["https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024090300","display_name":"Mohamed\u2013Chaker Larabi","orcid":"https://orcid.org/0000-0003-4511-5381"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mohamed-Chaker Larabi","raw_affiliation_strings":["CNRS, Univ. Poitiers,XLIM, UMR 7252,France"],"affiliations":[{"raw_affiliation_string":"CNRS, Univ. Poitiers,XLIM, UMR 7252,France","institution_ids":["https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013870013","display_name":"Seif-Eddine Benkabou","orcid":"https://orcid.org/0000-0002-4526-534X"},"institutions":[{"id":"https://openalex.org/I32881790","display_name":"Universit\u00e9 de Poitiers","ror":"https://ror.org/04xhy8q59","country_code":"FR","type":"education","lineage":["https://openalex.org/I32881790"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Seif-Eddine Benkabou","raw_affiliation_strings":["Univ. Poitiers,LIAS,France"],"affiliations":[{"raw_affiliation_string":"Univ. Poitiers,LIAS,France","institution_ids":["https://openalex.org/I32881790"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036140037"],"corresponding_institution_ids":["https://openalex.org/I1294671590"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16453678,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":1.0,"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":1.0,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9961000084877014,"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":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7941339015960693},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6364444494247437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6308619379997253},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5627914071083069},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5319163203239441},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.517737090587616},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5084825754165649},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5074333548545837},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4902830421924591},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47371476888656616},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42358750104904175},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4219497740268707},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4192984402179718},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3937130272388458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7941339015960693},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6364444494247437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6308619379997253},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5627914071083069},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5319163203239441},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.517737090587616},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5084825754165649},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5074333548545837},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4902830421924591},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47371476888656616},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42358750104904175},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4219497740268707},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4192984402179718},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3937130272388458},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mmsp59012.2023.10337664","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mmsp59012.2023.10337664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04729225v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04729225","pdf_url":"https://hal.science/hal-04729225/document","source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/10337664","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04729225v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04729225","pdf_url":"https://hal.science/hal-04729225/document","source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/10337664","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325796","display_name":"Conseil R\u00e9gional Aquitaine","ror":"https://ror.org/01wjxf448"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389474417.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1552073401","https://openalex.org/W2085518012","https://openalex.org/W2119999314","https://openalex.org/W2162220380","https://openalex.org/W2162692770","https://openalex.org/W2194775991","https://openalex.org/W2754213847","https://openalex.org/W2799653921","https://openalex.org/W2905544033","https://openalex.org/W2990391914","https://openalex.org/W2993382191","https://openalex.org/W3035712445","https://openalex.org/W3103635814","https://openalex.org/W3162407014","https://openalex.org/W3166201206","https://openalex.org/W3182123567","https://openalex.org/W3194280054","https://openalex.org/W4214745154","https://openalex.org/W4292830150","https://openalex.org/W4304098335","https://openalex.org/W4317796340","https://openalex.org/W4366989183","https://openalex.org/W4375868784","https://openalex.org/W4392531858","https://openalex.org/W6780415784"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W2743738614"],"abstract_inverted_index":{"Assessing":[0],"the":[1,44,79,86,123,140,176],"quality":[2,31,72,131,181],"of":[3,16,46,67,100,127,178],"360-degree":[4,40,80,129,179],"images":[5],"based":[6],"on":[7,139,157],"individual":[8,93],"regions":[9,24],"presents":[10],"a":[11,54,65,96],"challenging":[12],"task.":[13],"The":[14,154],"lack":[15],"ground":[17],"truth":[18],"opinion":[19],"scores":[20],"(MOS)":[21],"for":[22,38,75,92,146],"specific":[23],"makes":[25],"it":[26],"difficult":[27],"to":[28,70,108,137],"evaluate":[29],"image":[30,130,180],"accurately.":[32],"Existing":[33],"datasets":[34,160],"only":[35],"provide":[36],"MOS":[37],"entire":[39],"images,":[41],"which":[42],"limits":[43],"granularity":[45],"assessment.":[47,132,182],"To":[48],"overcome":[49],"this":[50],"challenge,":[51],"we":[52,104,121],"propose":[53],"novel":[55],"framework":[56],"that":[57,162],"employs":[58],"adaptive":[59,163],"patch":[60,77,101,164],"labeling":[61,165],"techniques.":[62],"We":[63],"leverage":[64],"set":[66],"2D-IQA":[68],"methods":[69],"generate":[71],"score":[73],"distributions":[74],"each":[76,147],"in":[78,150],"images.":[81],"These":[82],"distributions,":[83],"combined":[84],"with":[85],"available":[87],"MOS,":[88],"serve":[89],"as":[90],"labels":[91,107],"patches,":[94],"providing":[95],"more":[97],"comprehensive":[98],"characterization":[99],"quality.":[102],"Furthermore,":[103],"use":[105],"these":[106],"adaptively":[109],"select":[110],"and":[111,125,143,166,171],"refine":[112],"deep":[113],"neural":[114],"features.":[115],"By":[116],"selectively":[117],"choosing":[118],"label-specific":[119],"features,":[120],"enhance":[122],"accuracy":[124],"effectiveness":[126],"patch-based":[128],"This":[133],"approach":[134],"allows":[135],"us":[136],"focus":[138],"most":[141],"relevant":[142],"informative":[144],"features":[145],"patch,":[148],"resulting":[149],"improved":[151],"assessment":[152],"performance.":[153],"experimental":[155],"results":[156],"two":[158],"benchmark":[159],"demonstrate":[161],"feature":[167],"selection":[168],"achieve":[169],"accurate":[170],"reliable":[172],"performances,":[173],"thus":[174],"advancing":[175],"field":[177]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}