{"id":"https://openalex.org/W7118191189","doi":"https://doi.org/10.1109/tmm.2026.3651128","title":"Distortion-Sensitive Masked Autoencoder for Omnidirectional Video Quality Assessment","display_name":"Distortion-Sensitive Masked Autoencoder for Omnidirectional Video Quality Assessment","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7118191189","doi":"https://doi.org/10.1109/tmm.2026.3651128"},"language":null,"primary_location":{"id":"doi:10.1109/tmm.2026.3651128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2026.3651128","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/A5063539409","display_name":"Zongyao Hu","orcid":"https://orcid.org/0000-0001-7095-3905"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongyao Hu","raw_affiliation_strings":["Beijing Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5896-1427","affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054530129","display_name":"Lixiong Liu","orcid":"https://orcid.org/0000-0001-8357-1113"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixiong Liu","raw_affiliation_strings":["Beijing Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8357-1113","affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101471360","display_name":"Ke Gu","orcid":"https://orcid.org/0000-0003-3726-0036"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Gu","raw_affiliation_strings":["School of Information Science and Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6903-184X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113876094","display_name":"Leida Li","orcid":"https://orcid.org/0000-0002-5418-9879"},"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’an, China"],"raw_orcid":"https://orcid.org/0000-0001-9069-8796","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075463806","display_name":"Alan C. Bovik","orcid":"https://orcid.org/0000-0001-6067-710X"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Conrad Bovik","raw_affiliation_strings":["Laboratory for Image and Video Engineering (LIVE), Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA"],"raw_orcid":"https://orcid.org/0000-0001-6067-710X","affiliations":[{"raw_affiliation_string":"Laboratory for Image and Video Engineering (LIVE), Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.6924,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96560799,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"28","issue":null,"first_page":"3353","last_page":"3363"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9961000084877014,"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"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","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/T10741","display_name":"Video Coding and Compression Technologies","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.0006000000284984708,"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/autoencoder","display_name":"Autoencoder","score":0.8654000163078308},{"id":"https://openalex.org/keywords/omnidirectional-antenna","display_name":"Omnidirectional antenna","score":0.8026999831199646},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5895000100135803},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5033000111579895},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.4846999943256378},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.46869999170303345},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39959999918937683},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.36910000443458557}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8654000163078308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8557000160217285},{"id":"https://openalex.org/C24027999","wikidata":"https://www.wikidata.org/wiki/Q2176348","display_name":"Omnidirectional antenna","level":3,"score":0.8026999831199646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6564000248908997},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5895000100135803},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5033000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49050000309944153},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.46869999170303345},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.3212999999523163},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3163999915122986},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.29660001397132874},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25619998574256897},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2026.3651128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2026.3651128","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":[],"awards":[{"id":"https://openalex.org/G1279083513","display_name":null,"funder_award_id":"62322302","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1544458871","display_name":null,"funder_award_id":"62132012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3967746883","display_name":null,"funder_award_id":"62372042","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4363399934","display_name":null,"funder_award_id":"62273011","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":69,"referenced_works":["https://openalex.org/W1973207880","https://openalex.org/W2048042940","https://openalex.org/W2063360098","https://openalex.org/W2073623229","https://openalex.org/W2117539524","https://openalex.org/W2172058006","https://openalex.org/W2194775991","https://openalex.org/W2473930607","https://openalex.org/W2562637781","https://openalex.org/W2733888878","https://openalex.org/W2766426813","https://openalex.org/W2777280533","https://openalex.org/W2916909316","https://openalex.org/W2965644659","https://openalex.org/W2990391914","https://openalex.org/W2990503944","https://openalex.org/W2997463005","https://openalex.org/W3005018151","https://openalex.org/W3020521460","https://openalex.org/W3030701471","https://openalex.org/W3035725276","https://openalex.org/W3048688174","https://openalex.org/W3091452821","https://openalex.org/W3093244794","https://openalex.org/W3094502228","https://openalex.org/W3095427077","https://openalex.org/W3096638576","https://openalex.org/W3113191828","https://openalex.org/W3115841380","https://openalex.org/W3118542935","https://openalex.org/W3167030277","https://openalex.org/W3199775471","https://openalex.org/W3212279368","https://openalex.org/W3212793811","https://openalex.org/W4200139856","https://openalex.org/W4225292576","https://openalex.org/W4225466252","https://openalex.org/W4282964635","https://openalex.org/W4285246882","https://openalex.org/W4293093523","https://openalex.org/W4296035682","https://openalex.org/W4296913481","https://openalex.org/W4297094443","https://openalex.org/W4312890925","https://openalex.org/W4313010977","https://openalex.org/W4313156423","https://openalex.org/W4313591426","https://openalex.org/W4385764089","https://openalex.org/W4386076402","https://openalex.org/W4386280774","https://openalex.org/W4386523589","https://openalex.org/W4387068132","https://openalex.org/W4387757530","https://openalex.org/W4387757549","https://openalex.org/W4388692378","https://openalex.org/W4389104669","https://openalex.org/W4390241502","https://openalex.org/W4390285150","https://openalex.org/W4390533518","https://openalex.org/W4390871630","https://openalex.org/W4392543651","https://openalex.org/W4392667279","https://openalex.org/W4393148324","https://openalex.org/W4402951668","https://openalex.org/W4402979257","https://openalex.org/W4404893085","https://openalex.org/W4404952931","https://openalex.org/W4406902947","https://openalex.org/W7133239857"],"related_works":[],"abstract_inverted_index":{"Omnidirectional":[0],"Video":[1],"Quality":[2],"Assessment":[3],"(OVQA)":[4],"is":[5,128,180,225],"a":[6,44,122,145,151,221],"challenging":[7],"task":[8,93],"due":[9],"to":[10,51,53,62,83,91,99,103,113,130,156,182,192,208],"the":[11,55,71,92,107,110,114,163,184,190,218,228],"limited":[12],"availability":[13],"of":[14,17,23,57,94,109,213,217],"adequate":[15],"numbers":[16],"training":[18,216],"samples":[19,61],"for":[20,79],"learning":[21,38],"representations":[22,42,158],"distortions":[24,133],"on":[25,134,159,241],"omnidirectional":[26,65,135,141,168],"videos.":[27,136],"The":[28,178,197,234,246],"recent":[29],"masked":[30,146,185],"autoencoder":[31,179],"(MAE)":[32],"has":[33],"shown":[34],"promising":[35],"performance":[36,254],"in":[37,43],"local":[39],"and":[40,47,105,143,150,200],"global":[41],"self-supervised":[45],"way,":[46],"can":[48],"be":[49],"used":[50],"attempt":[52],"mitigate":[54,209],"difficulty":[56],"having":[58],"insufficient":[59],"annotated":[60],"adequately":[63],"train":[64],"video":[66,195],"quality":[67],"prediction":[68],"models.":[69,258],"But":[70],"reconstruction":[72],"tasks":[73],"that":[74,127,250],"MAE":[75,111],"models":[76],"are":[77,170,205],"designed":[78],"do":[80],"not":[81],"pertain":[82],"predicting":[84],"diverse":[85,194],"perceptual":[86,132],"distortions,":[87,186],"especially":[88],"those":[89],"relevant":[90],"OVQA.":[95],"We":[96],"have":[97],"attempted":[98],"overcome":[100],"these":[101],"limitations":[102],"harness":[104],"apply":[106],"power":[108],"concept":[112],"OVQA":[115,223,244],"problem.":[116],"Towards":[117],"this":[118],"purpose,":[119],"we":[120],"create":[121],"Distortion-Sensitive":[123],"Masked":[124],"AutoEncoder":[125],"(DS-MAE)":[126],"able":[129],"represent":[131,193],"DS-MAE":[137,230],"extracts":[138,199],"viewports":[139],"from":[140,167],"videos":[142,169],"employs":[144],"autoencoding":[147],"module":[148,154],"(MAM)":[149],"knowledge":[152],"replay":[153],"(KRM)":[155],"learn":[157],"each":[160],"viewport.":[161],"In":[162],"MAM,":[164],"distorted":[165],"patches":[166],"masked,":[171],"by":[172],"replacing":[173],"them":[174,188],"with":[175,189],"undistorted":[176],"counterparts.":[177],"trained":[181],"reconstruct":[183],"imbuing":[187],"ability":[191],"degradations.":[196],"KRM":[198],"stores":[201],"content":[202,214],"representations,":[203],"which":[204],"then":[206],"\u201creplayed\u201d":[207],"potential":[210],"catastrophic":[211],"forgetting":[212],"during":[215],"DS-MAE.":[219],"Finally,":[220],"simple":[222],"model":[224],"constructed":[226],"using":[227],"pre-trained":[229],"across":[231],"all":[232,256],"viewports.":[233],"new":[235],"model,":[236],"called":[237],"OmniVQA,":[238],"was":[239],"tested":[240],"three":[242],"public":[243],"datasets.":[245],"experimental":[247],"results":[248],"show":[249],"OmniVQA":[251],"delivers":[252],"competitive":[253],"against":[255],"compared":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-05T00:00:00"}