{"id":"https://openalex.org/W3156760976","doi":"https://doi.org/10.1109/tmm.2021.3076612","title":"A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline","display_name":"A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline","publication_year":2021,"publication_date":"2021-04-30","ids":{"openalex":"https://openalex.org/W3156760976","doi":"https://doi.org/10.1109/tmm.2021.3076612","mag":"3156760976"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2021.3076612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3076612","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.04443","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yingying Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingying Zhao","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mingzhi Dong","orcid":"https://orcid.org/0000-0001-5902-1306"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhi Dong","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yujiang Wang","orcid":"https://orcid.org/0000-0002-6220-029X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yujiang Wang","raw_affiliation_strings":["Department of Computing, Imperial College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Da Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Feng","raw_affiliation_strings":["Alibaba (Beijing) Software Service Company Limited, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba (Beijing) Software Service Company Limited, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qin Lv","orcid":null},"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":"Qin Lv","raw_affiliation_strings":["University of Colorado Boulder, Boulder, CO, USA"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Robert P. Dick","orcid":"https://orcid.org/0000-0001-5428-9530"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert P. Dick","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science College of Engineering, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science College of Engineering, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0003-3103-8442"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Li","raw_affiliation_strings":["Microsoft Research Asia, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Shanghai, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tun Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tun Lu","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ning Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Gu","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":null,"display_name":"Li Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Shang","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.6782,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.70583755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"24","issue":null,"first_page":"2150","last_page":"2163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.16169999539852142,"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":0.16169999539852142,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.13120000064373016,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.07020000368356705,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/analytics","display_name":"Analytics","score":0.6771000027656555},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.524399995803833},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.49390000104904175},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4352000057697296},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.4271000027656555},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.4196000099182129},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.4092999994754791},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.38100001215934753}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8659999966621399},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44040000438690186},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.44020000100135803},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4352000057697296},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.4271000027656555},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C2778598663","wikidata":"https://www.wikidata.org/wiki/Q1407599","display_name":"Video content analysis","level":4,"score":0.36629998683929443},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34209999442100525},{"id":"https://openalex.org/C117090137","wikidata":"https://www.wikidata.org/wiki/Q7927977","display_name":"Video post-processing","level":5,"score":0.33070001006126404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32420000433921814},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.30219998955726624},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2768000066280365},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C162478608","wikidata":"https://www.wikidata.org/wiki/Q4011369","display_name":"Uncompressed video","level":4,"score":0.27239999175071716},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2599000036716461}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2021.3076612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3076612","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"},{"id":"pmh:oai:arXiv.org:2104.04443","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.04443","pdf_url":"https://arxiv.org/pdf/2104.04443","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2104.04443","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.04443","pdf_url":"https://arxiv.org/pdf/2104.04443","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W764651262","https://openalex.org/W2111200615","https://openalex.org/W2145339207","https://openalex.org/W2155968351","https://openalex.org/W2167993212","https://openalex.org/W2194775991","https://openalex.org/W2552900565","https://openalex.org/W2560474170","https://openalex.org/W2739669104","https://openalex.org/W2777460464","https://openalex.org/W2884732669","https://openalex.org/W2897264331","https://openalex.org/W2908138940","https://openalex.org/W2945855225","https://openalex.org/W2954684697","https://openalex.org/W2956100049","https://openalex.org/W2963150697","https://openalex.org/W2963445119","https://openalex.org/W2963566548","https://openalex.org/W2982723417","https://openalex.org/W2991680749","https://openalex.org/W3009458003","https://openalex.org/W3035950208","https://openalex.org/W6631190155","https://openalex.org/W6743555153","https://openalex.org/W6779448426"],"related_works":[],"abstract_inverted_index":{"Deep-learning-based":[0],"video":[1,12,49,67,98,113,120,140,176],"processing":[2],"has":[3],"yielded":[4],"transformative":[5],"results":[6],"in":[7,32,48],"recent":[8],"years.":[9],"However,":[10],"the":[11,37,62,74,90,96,103,109,117,123,129,136,156,183,202],"analytics":[13,68,99,114,121],"pipeline":[14],"is":[15,153,173,180],"energy-intensive":[16],"due":[17],"to":[18,60,87,142,158,165,175],"high":[19,40],"data":[20,50,76],"rates":[21],"and":[22,41,45,54,93,189],"reliance":[23],"on":[24,108,201],"complex":[25],"inference":[26],"algorithms,":[27],"which":[28,179],"limits":[29],"its":[30],"adoption":[31],"energy-constrained":[33],"applications.":[34],"Motivated":[35],"by":[36,148],"observation":[38],"of":[39,65,71,78,95,105,111,119,138,182,198],"variable":[42],"spatial":[43],"redundancy":[44,162],"temporal":[46],"dynamics":[47],"streams,":[51],"we":[52],"design":[53],"evaluate":[55],"an":[56],"adaptive-resolution":[57],"optimization":[58,126],"framework":[59,82,127,157,172],"minimize":[61,159],"energy":[63,145,192],"use":[64],"multi-task":[66],"pipelines.":[69],"Instead":[70],"heuristically":[72],"tuning":[73],"input":[75,91,139],"resolution":[77,92,107,137],"individual":[79],"tasks,":[80,188],"our":[81],"utilizes":[83],"deep":[84],"reinforcement":[85,149],"learning":[86],"dynamically":[88,134],"govern":[89],"computation":[94],"entire":[97],"pipeline.":[100],"By":[101],"monitoring":[102],"impact":[104],"varying":[106],"quality":[110],"high-dimensional":[112],"features,":[115],"hence":[116],"accuracy":[118,200],"results,":[122],"proposed":[124,171],"end-to-end":[125],"learns":[128],"best":[130],"non-myopic":[131],"policy":[132],"for":[133],"controlling":[135],"streams":[141],"globally":[143],"optimize":[144],"efficiency.":[146],"Governed":[147],"learning,":[150],"optical":[151],"flow":[152],"incorporated":[154],"into":[155],"unnecessary":[160],"spatio-temporal":[161],"that":[163],"leads":[164],"re-computation,":[166],"while":[167],"preserving":[168],"accuracy.":[169],"The":[170],"applied":[174],"instance":[177],"segmentation":[178],"one":[181],"most":[184],"challenging":[185],"computer":[186],"vision":[187],"achieves":[190],"better":[191],"efficiency":[193],"than":[194],"all":[195],"baseline":[196],"methods":[197],"similar":[199],"YouTube-VIS":[203],"dataset.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2021-04-26T00:00:00"}