{"id":"https://openalex.org/W7106263081","doi":"https://doi.org/10.1145/3680207.3765252","title":"EOS: Energy-Optimized Super-Resolution on Mobile Devices for Live 360-Degree Videos","display_name":"EOS: Energy-Optimized Super-Resolution on Mobile Devices for Live 360-Degree Videos","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W7106263081","doi":"https://doi.org/10.1145/3680207.3765252"},"language":"en","primary_location":{"id":"doi:10.1145/3680207.3765252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680207.3765252","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680207.3765252","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3680207.3765252","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Seonghoon Park","orcid":"https://orcid.org/0000-0002-7336-6295"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seonghoon Park","raw_affiliation_strings":["Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-7336-6295","affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minchan Kim","orcid":"https://orcid.org/0009-0008-4710-3812"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minchan Kim","raw_affiliation_strings":["Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-4710-3812","affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hyejin Park","orcid":"https://orcid.org/0009-0006-3000-8638"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyejin Park","raw_affiliation_strings":["Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0006-3000-8638","affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jeho Lee","orcid":"https://orcid.org/0000-0002-9035-2602"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeho Lee","raw_affiliation_strings":["Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-9035-2602","affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiwon Kim","orcid":"https://orcid.org/0000-0002-5182-2667"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Jiwon Kim","raw_affiliation_strings":["Uppsala University, Uppsala, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-5182-2667","affiliations":[{"raw_affiliation_string":"Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hojung Cha","orcid":"https://orcid.org/0000-0002-9060-5091"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hojung Cha","raw_affiliation_strings":["Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-9060-5091","affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52345269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"878","last_page":"893"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.906000018119812,"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":0.906000018119812,"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":0.05139999836683273,"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":0.022099999710917473,"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/mobile-device","display_name":"Mobile device","score":0.6732000112533569},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.532800018787384},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5268999934196472},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47540000081062317},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.45680001378059387},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.44999998807907104},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.444599986076355},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4050999879837036},{"id":"https://openalex.org/keywords/mobile-telephony","display_name":"Mobile telephony","score":0.37860000133514404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802000045776367},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.6732000112533569},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.532800018787384},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5299000144004822},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.45680001378059387},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.44999998807907104},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.444599986076355},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4050999879837036},{"id":"https://openalex.org/C95491727","wikidata":"https://www.wikidata.org/wiki/Q992968","display_name":"Mobile telephony","level":3,"score":0.37860000133514404},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3357999920845032},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3212999999523163},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C134535813","wikidata":"https://www.wikidata.org/wiki/Q1888734","display_name":"Transcoding","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3680207.3765252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680207.3765252","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680207.3765252","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:uu-575070","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-575070","pdf_url":null,"source":{"id":"https://openalex.org/S4306400653","display_name":"Diva portal (Dalarna University Library)","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":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3680207.3765252","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680207.3765252","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680207.3765252","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8903680443763733,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2325587046","display_name":null,"funder_award_id":"RS-2018-II180532","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G7135983821","display_name":null,"funder_award_id":"RS-2024-00344323","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7106263081.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W2046119925","https://openalex.org/W2117804578","https://openalex.org/W2194775991","https://openalex.org/W2557227117","https://openalex.org/W2734981703","https://openalex.org/W2898855235","https://openalex.org/W2950297857","https://openalex.org/W2962785568","https://openalex.org/W2963446712","https://openalex.org/W2979863766","https://openalex.org/W2998611528","https://openalex.org/W3046761316","https://openalex.org/W3047354607","https://openalex.org/W3087814885","https://openalex.org/W3174119208","https://openalex.org/W3175197158","https://openalex.org/W3176583247","https://openalex.org/W4225163840","https://openalex.org/W4290098629","https://openalex.org/W4290991273","https://openalex.org/W4304098311","https://openalex.org/W4312510024","https://openalex.org/W4312549026","https://openalex.org/W4313306251","https://openalex.org/W4367046660","https://openalex.org/W4380928775","https://openalex.org/W4382240745","https://openalex.org/W4383704293","https://openalex.org/W4385815473","https://openalex.org/W4386243250","https://openalex.org/W4386260640","https://openalex.org/W4392472215","https://openalex.org/W4399117225","https://openalex.org/W4399801897","https://openalex.org/W4401325834","https://openalex.org/W4401508456","https://openalex.org/W4401726143","https://openalex.org/W4401943268","https://openalex.org/W4402916042","https://openalex.org/W4403780714","https://openalex.org/W4405014410","https://openalex.org/W4408954808","https://openalex.org/W4410068044","https://openalex.org/W4410428100","https://openalex.org/W4412841381","https://openalex.org/W4414508187"],"related_works":[],"abstract_inverted_index":{"Although":[0],"on-device":[1,30],"video":[2,36],"super-resolution":[3,31,47,133],"enables":[4],"high-quality":[5],"live":[6,38,94],"360-degree":[7],"streaming":[8],"on":[9,50,159],"mobile":[10,34,92,122],"devices,":[11,123],"existing":[12],"methods":[13],"often":[14],"waste":[15,43],"energy":[16,42,71],"by":[17,44,169],"overlooking":[18],"perceived":[19],"visual":[20,53,86,145,178],"quality.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25],"present":[26],"EOS,":[27],"an":[28,65,125],"energy-efficient":[29],"system":[32],"for":[33,121],"omnidirectional":[35],"(ODV)":[37],"streaming.":[39,95],"EOS":[40,100,102,111,164],"reduces":[41,165],"dynamically":[45],"adjusting":[46],"complexity":[48],"based":[49],"the":[51,89,131],"predicted":[52],"quality":[54,87,146,179],"of":[55,91],"super-resolved":[56],"frames.":[57],"This":[58],"approach":[59],"raises":[60],"two":[61],"challenges:":[62],"(1)":[63],"designing":[64],"adaptive":[66],"inference":[67],"policy":[68],"that":[69,128,163],"maximizes":[70],"savings":[72],"while":[73,175],"minimizing":[74],"degradation":[75],"in":[76,150],"Quality-of-Experience":[77],"(QoE),":[78],"and":[79,104,135,180],"(2)":[80],"developing":[81],"a":[82,105,114],"method":[83],"to":[84,172],"predict":[85],"under":[88],"constraints":[90],"ODV":[93],"To":[96],"tackle":[97],"these":[98],"challenges,":[99],"introduces":[101],"SR":[103,112],"No-Reference":[106,139],"Up-scaling":[107],"Quality":[108,141],"Prediction":[109,142],"scheme.":[110],"employs":[113],"device-agnostic,":[115],"scalable":[116],"deep":[117],"neural":[118],"network":[119],"optimized":[120],"with":[124],"energy-aware":[126],"scheduler":[127],"jointly":[129],"selects":[130],"optimal":[132],"model":[134],"GPU":[136],"frequency.":[137],"The":[138],"Upscaling":[140],"scheme":[143],"estimates":[144],"across":[147],"arbitrary":[148],"viewpoints":[149],"real":[151],"time":[152],"without":[153],"requiring":[154],"high-resolution":[155],"reference":[156],"videos.":[157],"Experiments":[158],"commodity":[160],"smartphones":[161],"show":[162],"average":[166],"power":[167],"consumption":[168],"34.6%\u201349.9%":[170],"compared":[171],"baseline":[173],"methods,":[174],"preserving":[176],"high":[177],"frame":[181],"rates.":[182]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-23T00:00:00"}
