{"id":"https://openalex.org/W4412030281","doi":"https://doi.org/10.1109/tcsvt.2025.3585993","title":"Blind Quality Assessment of Wide-Angle Videos Based on Deformation Representation Learning and Multi-Dimensional Feature Fusion","display_name":"Blind Quality Assessment of Wide-Angle Videos Based on Deformation Representation Learning and Multi-Dimensional Feature Fusion","publication_year":2025,"publication_date":"2025-07-04","ids":{"openalex":"https://openalex.org/W4412030281","doi":"https://doi.org/10.1109/tcsvt.2025.3585993"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2025.3585993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3585993","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5101549477","display_name":"Bo Hu","orcid":"https://orcid.org/0000-0002-1842-2856"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Hu","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100678134","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-6726-5738"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"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&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;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&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059540876","display_name":"Wen Lu","orcid":"https://orcid.org/0000-0002-8193-6016"},"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":"Wen Lu","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101549477"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13847564,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"12","first_page":"12227","last_page":"12237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14158","display_name":"Optical Systems and Laser Technology","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14158","display_name":"Optical Systems and Laser Technology","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9796000123023987,"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/T13579","display_name":"Image and Video Stabilization","score":0.9681000113487244,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602472066879272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.637115478515625},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5489979386329651},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5333459377288818},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5031546950340271},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4963551163673401},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4878842830657959},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47364985942840576},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4713045060634613},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46537017822265625},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4595469832420349},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.44496914744377136},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.43045246601104736},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.20080962777137756},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19908574223518372},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09640440344810486}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602472066879272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.637115478515625},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5489979386329651},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5333459377288818},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5031546950340271},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4963551163673401},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4878842830657959},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47364985942840576},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4713045060634613},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46537017822265625},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4595469832420349},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.44496914744377136},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.43045246601104736},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.20080962777137756},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19908574223518372},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09640440344810486},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2025.3585993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3585993","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1143917335","display_name":null,"funder_award_id":"62471349","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1391376299","display_name":null,"funder_award_id":"CSTB2023NSCQ-LZX0085","funder_id":"https://openalex.org/F4320336213","funder_display_name":"National Natural Science Foundation of China-Guangdong Joint Fund"},{"id":"https://openalex.org/G2526437637","display_name":null,"funder_award_id":"CSTB2023NSCQ-BHX0187","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G3145998761","display_name":null,"funder_award_id":"62101084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6468169989","display_name":null,"funder_award_id":"62171340","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"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336213","display_name":"National Natural Science Foundation of China-Guangdong Joint Fund","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1982471090","https://openalex.org/W2028898066","https://openalex.org/W2063658831","https://openalex.org/W2101144220","https://openalex.org/W2129644086","https://openalex.org/W2162692770","https://openalex.org/W2194775991","https://openalex.org/W2592756114","https://openalex.org/W2611434713","https://openalex.org/W2791258091","https://openalex.org/W2810069535","https://openalex.org/W2886645798","https://openalex.org/W2888360040","https://openalex.org/W2914658805","https://openalex.org/W2950154603","https://openalex.org/W2965644659","https://openalex.org/W2979543786","https://openalex.org/W3000169940","https://openalex.org/W3016028173","https://openalex.org/W3030701471","https://openalex.org/W3093244794","https://openalex.org/W3093431261","https://openalex.org/W3133605536","https://openalex.org/W3159397114","https://openalex.org/W3169674094","https://openalex.org/W3174437687","https://openalex.org/W3174722860","https://openalex.org/W3193919962","https://openalex.org/W3195201937","https://openalex.org/W3206968390","https://openalex.org/W4200352615","https://openalex.org/W4225292576","https://openalex.org/W4226145929","https://openalex.org/W4281846337","https://openalex.org/W4296913481","https://openalex.org/W4308237307","https://openalex.org/W4312818079","https://openalex.org/W4322706707","https://openalex.org/W4375929089","https://openalex.org/W4385800789","https://openalex.org/W4386057769","https://openalex.org/W4386071544","https://openalex.org/W4386766876","https://openalex.org/W4387609141","https://openalex.org/W4387968291","https://openalex.org/W4388499609","https://openalex.org/W4390874113","https://openalex.org/W4392125885","https://openalex.org/W4392667279","https://openalex.org/W4392939676","https://openalex.org/W4401726215","https://openalex.org/W4401878802","https://openalex.org/W4402753893","https://openalex.org/W4402769976","https://openalex.org/W4402772655","https://openalex.org/W4408352131"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3214791684","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969"],"abstract_inverted_index":{"Wide-angle":[0],"videos":[1,89],"shot":[2],"with":[3],"short-focus":[4],"lenses":[5],"often":[6],"exhibit":[7],"deformation":[8,41,70,84,93,126,134],"distortions,":[9],"which":[10],"poses":[11],"significant":[12],"challenges":[13],"for":[14],"video":[15,26,48,64,101,201],"quality":[16,65],"assessment":[17,66,104],"(VQA).":[18],"Although":[19],"current":[20],"VQA":[21,197],"methods":[22],"focus":[23],"primarily":[24],"on":[25,37,43,69,91,97,195],"content":[27],"and":[28,73,103,130,152,159,186,190,199,215],"distortion":[29,160],"perception,":[30],"there":[31],"has":[32],"been":[33],"little":[34],"explicit":[35],"research":[36],"the":[38,44,56,83,92,115,141,154,205,208],"impact":[39],"of":[40,46,87,118,144,212],"characteristics":[42,86],"perception":[45,102,142],"wide-angle":[47,63,88,196],"quality.":[49],"To":[50],"this":[51,53],"end,":[52],"paper":[54],"makes":[55],"first":[57,81,109],"attempt":[58],"to":[59,182],"construct":[60],"a":[61,99],"novel":[62],"method":[67],"based":[68,90],"representation":[71,135],"learning":[72,136],"multi-dimensional":[74,176],"feature":[75,177],"fusion,":[76],"termed":[77],"DRLMF.":[78],"Specifically,":[79],"we":[80],"analyze":[82],"distribution":[85],"camera":[94],"model.":[95],"Based":[96],"this,":[98],"three-stream":[100],"network":[105],"is":[106,180],"proposed.":[107],"The":[108,120,162,217],"branch":[110,122,164],"extracts":[111,165],"global":[112],"semantics":[113],"using":[114,168],"image":[116],"encoder":[117],"CLIP.":[119],"second":[121],"introduces":[123],"an":[124,132,169,174],"effective":[125,175],"region":[127],"selection":[128],"strategy":[129],"proposes":[131],"interpretable":[133],"module.":[137],"This":[138],"module":[139,179],"leverages":[140],"advantages":[143],"convolutional":[145],"neural":[146],"networks":[147],"(CNNs)":[148],"in":[149,210],"local":[150],"distortions":[151],"considers":[153],"correlation":[155],"between":[156],"patch":[157],"size":[158],"perception.":[161],"third":[163],"motion":[166,191],"features":[167],"action":[170],"recognition":[171],"network.":[172],"Finally,":[173],"fusion":[178],"proposed":[181],"integrate":[183],"more":[184],"refined":[185],"richer":[187],"semantic,":[188],"deformation,":[189],"features.":[192],"Extensive":[193],"experiments":[194],"datasets":[198,202],"standard":[200],"show":[203],"that":[204],"DRLMF":[206],"outperforms":[207],"state-of-the-arts":[209],"terms":[211],"prediction":[213],"monotonicity":[214],"accuracy.":[216],"codes":[218],"will":[219],"be":[220],"available":[221],"at":[222],"https://github.com/BoHu90/DRLMF.":[223]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
