{"id":"https://openalex.org/W3090186123","doi":"https://doi.org/10.1109/iscas45731.2020.9180452","title":"Memory-Augmented Auto-Regressive Network for Frame Recurrent Inter Prediction","display_name":"Memory-Augmented Auto-Regressive Network for Frame Recurrent Inter Prediction","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3090186123","doi":"https://doi.org/10.1109/iscas45731.2020.9180452","mag":"3090186123"},"language":"en","primary_location":{"id":"doi:10.1109/iscas45731.2020.9180452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5064024724","display_name":"Yuzhang Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhang Hu","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University","Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054386013","display_name":"Sifeng Xia","orcid":"https://orcid.org/0000-0003-0301-0004"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sifeng Xia","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University","Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070884682","display_name":"Wenhan Yang","orcid":"https://orcid.org/0000-0002-1692-0069"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhan Yang","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University","Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761525","display_name":"Jiaying Liu","orcid":"https://orcid.org/0000-0002-0468-9576"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaying Liu","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University","Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.1709,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.47468331,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9973999857902527,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9973999857902527,"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":0.9944000244140625,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9879999756813049,"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/computer-science","display_name":"Computer science","score":0.7337973713874817},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5596184134483337},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.48199597001075745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37800002098083496},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20150569081306458},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.13520297408103943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07689371705055237}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7337973713874817},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5596184134483337},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.48199597001075745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37800002098083496},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20150569081306458},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.13520297408103943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07689371705055237}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas45731.2020.9180452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W648143168","https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W2024353898","https://openalex.org/W2035038275","https://openalex.org/W2140199336","https://openalex.org/W2146395539","https://openalex.org/W2401640538","https://openalex.org/W2565764649","https://openalex.org/W2586480386","https://openalex.org/W2604329646","https://openalex.org/W2884800852","https://openalex.org/W2901921200","https://openalex.org/W2940542968","https://openalex.org/W2951523806","https://openalex.org/W2962737519","https://openalex.org/W2962930383","https://openalex.org/W2963003152","https://openalex.org/W2963109922","https://openalex.org/W2964121744","https://openalex.org/W2964203072","https://openalex.org/W2964251418","https://openalex.org/W2995368614","https://openalex.org/W2997829087","https://openalex.org/W2998788130","https://openalex.org/W3102015846","https://openalex.org/W4294554810","https://openalex.org/W6621378261","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6704826028","https://openalex.org/W6713563955","https://openalex.org/W6735698919","https://openalex.org/W6756858095","https://openalex.org/W6770862486","https://openalex.org/W6785343060"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2171218219","https://openalex.org/W1972271943","https://openalex.org/W2150410159","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W3150905897","https://openalex.org/W4327525404","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Inter":[0],"prediction":[1,78],"is":[2,145],"quite":[3],"important":[4],"for":[5,28,76,147,174],"the":[6,37,55,84,99,119,135,148,156,175,179],"modern":[7],"codecs":[8],"to":[9,31,43,59,96,170],"remove":[10],"temporal":[11,50,103,149],"redundancy.":[12],"In":[13],"this":[14],"paper,":[15],"we":[16,69],"make":[17],"endeavors":[18],"in":[19,79],"generating":[20],"artificial":[21,65],"reference":[22,47,66],"frames":[23,27,90],"with":[24,87,138],"previous":[25],"reconstructed":[26,153],"inter":[29],"prediction,":[30],"offer":[32],"a":[33,45,71,127,141],"better":[34,97],"choice":[35],"when":[36],"traditional":[38],"block-wise":[39],"motion":[40,121],"estimation":[41],"fails":[42],"find":[44],"good":[46],"block.":[48],"Long-term":[49],"dynamics":[51,122],"are":[52,109],"tracked":[53],"during":[54],"whole":[56],"coding":[57],"process":[58],"generate":[60,134],"more":[61],"accurate":[62],"and":[63,102,124,168],"realistic":[64],"frames.":[67,154],"Specifically,":[68],"propose":[70],"Memory-Augmented":[72],"Auto-Regressive":[73],"Network":[74],"(MAAR-Net)":[75],"frame":[77,86,114,137],"video":[80],"coding.":[81],"MAAR-Net":[82],"regresses":[83],"current":[85],"two":[88],"nearest":[89],"via":[91],"an":[92],"auto-regressive":[93],"(AR)":[94],"model":[95],"capture":[98],"main":[100],"spatial":[101],"structures.":[104],"The":[105],"AR":[106],"regression":[107],"coefficients":[108],"generated":[110],"based":[111],"on":[112,163],"adjacent":[113],"information":[115],"as":[116,118],"well":[117],"long-term":[120],"accumulated":[123],"propagated":[125],"by":[126],"convolutional":[128],"Long":[129],"Short-Term":[130],"Memory":[131],"(LSTM).":[132],"To":[133],"target":[136],"higher":[139],"quality,":[140],"quality":[142],"attention":[143],"mechanism":[144],"introduced":[146],"regularization":[150],"between":[151],"different":[152],"With":[155],"well-designed":[157],"network,":[158],"our":[159],"method":[160],"surpasses":[161],"HEVC":[162],"average":[164],"4.0%":[165],"BD-rate":[166,172],"saving":[167,173],"up":[169],"10.6%":[171],"luma":[176],"component":[177],"under":[178],"low-delay":[180],"configuration.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}