{"id":"https://openalex.org/W3000016557","doi":"https://doi.org/10.1109/pcs48520.2019.8954565","title":"A CNN-based In-loop Filtering Approach for AV1 Video Codec","display_name":"A CNN-based In-loop Filtering Approach for AV1 Video Codec","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3000016557","doi":"https://doi.org/10.1109/pcs48520.2019.8954565","mag":"3000016557"},"language":"en","primary_location":{"id":"doi:10.1109/pcs48520.2019.8954565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs48520.2019.8954565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Picture Coding Symposium (PCS)","raw_type":"proceedings-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/A5028059517","display_name":"Dandan Ding","orcid":"https://orcid.org/0000-0003-2911-1321"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Ding","raw_affiliation_strings":["Hangzhou Normal University,Hangzhou,China","Hangzhou Normal University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]},{"raw_affiliation_string":"Hangzhou Normal University, Hangzhou, China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101970918","display_name":"Guangyao Chen","orcid":"https://orcid.org/0000-0002-6351-9083"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyao Chen","raw_affiliation_strings":["Hangzhou Normal University,Hangzhou,China","Hangzhou Normal University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]},{"raw_affiliation_string":"Hangzhou Normal University, Hangzhou, China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024859042","display_name":"Debargha Mukherjee","orcid":"https://orcid.org/0000-0002-9380-7377"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debargha Mukherjee","raw_affiliation_strings":["Google Inc.,Mountain View,United States","Google Inc., Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc.,Mountain View,United States","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Inc., Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036896344","display_name":"Urvang Joshi","orcid":"https://orcid.org/0000-0001-9590-9505"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Urvang Joshi","raw_affiliation_strings":["Google Inc.,Mountain View,United States","Google Inc., Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc.,Mountain View,United States","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Inc., Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077937114","display_name":"Yue Chen","orcid":"https://orcid.org/0000-0002-0190-5253"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Chen","raw_affiliation_strings":["Google Inc.,Mountain View,United States","Google Inc., Mountain View, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc.,Mountain View,United States","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Inc., Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5955,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.73077673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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":0.8152897357940674},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.6754803657531738},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6575247049331665},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6276218295097351},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5521805882453918},{"id":"https://openalex.org/keywords/coding-tree-unit","display_name":"Coding tree unit","score":0.4849989116191864},{"id":"https://openalex.org/keywords/algorithmic-efficiency","display_name":"Algorithmic efficiency","score":0.4761883318424225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45241519808769226},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4185049831867218},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3211709260940552},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30119985342025757},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.27575382590293884},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.10104694962501526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0970299243927002}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8152897357940674},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.6754803657531738},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6575247049331665},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6276218295097351},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5521805882453918},{"id":"https://openalex.org/C190750250","wikidata":"https://www.wikidata.org/wiki/Q13533439","display_name":"Coding tree unit","level":3,"score":0.4849989116191864},{"id":"https://openalex.org/C116709606","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Algorithmic efficiency","level":3,"score":0.4761883318424225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45241519808769226},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4185049831867218},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3211709260940552},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30119985342025757},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.27575382590293884},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.10104694962501526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0970299243927002},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/pcs48520.2019.8954565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs48520.2019.8954565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},{"id":"mag:3041189930","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002249208521003","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2242218935","https://openalex.org/W2302255633","https://openalex.org/W2477177239","https://openalex.org/W2510648513","https://openalex.org/W2530579199","https://openalex.org/W2612222456","https://openalex.org/W2739757502","https://openalex.org/W2752154940","https://openalex.org/W2791542696","https://openalex.org/W2792186562","https://openalex.org/W2792766850","https://openalex.org/W2793408333","https://openalex.org/W2799309438","https://openalex.org/W2890409760","https://openalex.org/W2890577598","https://openalex.org/W2964157487","https://openalex.org/W3100087914","https://openalex.org/W3102974666","https://openalex.org/W3104772632","https://openalex.org/W6698183232","https://openalex.org/W6728516736"],"related_works":["https://openalex.org/W2403124343","https://openalex.org/W1987778158","https://openalex.org/W4362519939","https://openalex.org/W2108288699","https://openalex.org/W4399356259","https://openalex.org/W2282705090","https://openalex.org/W2551340648","https://openalex.org/W2010408989","https://openalex.org/W4388069711","https://openalex.org/W2235484757"],"abstract_inverted_index":{"In-loop":[0],"filter":[1],"using":[2],"Convolutional":[3],"Neural":[4],"Network":[5],"(CNN)":[6],"has":[7],"lately":[8],"attracted":[9],"lots":[10],"of":[11,74,83,137,155],"attention":[12],"in":[13,30,42,55,160],"video":[14,121],"coding.":[15,57,71],"CNN":[16],"models":[17],"may":[18],"be":[19],"trained":[20],"to":[21,24,50,116,148],"learn":[22],"how":[23],"restore":[25],"degradation":[26],"introduced":[27],"by":[28],"compression":[29],"pictures,":[31],"and":[32,69,102,139,143,153],"hence":[33],"effectively":[34],"help":[35],"improve":[36],"the":[37,80,99,103],"coding":[38,100,122],"efficiency.":[39],"State-of-the-art":[40],"work":[41],"this":[43,59],"field":[44],"generally":[45],"employs":[46],"a":[47,63,89,118],"single":[48],"network":[49,65,76],"enhance":[51],"reconstructed":[52,84],"frames":[53],"mainly":[54],"intra":[56,68,142],"In":[58],"paper,":[60],"we":[61,87],"develop":[62],"depth-variable":[64],"handling":[66],"both":[67,98],"inter":[70,94,144],"The":[72,151],"depth":[73],"our":[75,114,130,156,161],"is":[77],"varied":[78],"with":[79],"distortion":[81],"levels":[82],"frames.":[85],"Moreover,":[86],"leverage":[88],"skip":[90],"enhancing":[91],"strategy":[92],"for":[93,141],"coding,":[95],"which":[96],"improves":[97],"efficiency":[101],"resulting":[104],"visual":[105],"quality,":[106],"while":[107],"maintaining":[108],"low":[109],"computational":[110],"complexity.":[111],"We":[112],"apply":[113],"approach":[115,131,157],"AV1,":[117],"newly":[119],"released":[120],"standard":[123],"from":[124],"AOM.":[125],"Experimental":[126],"results":[127],"show":[128],"that":[129],"achieves":[132],"an":[133],"average":[134],"BD-rate":[135],"reduction":[136],"7.27%":[138],"5.57%":[140],"modes,":[145],"respectively,":[146],"compared":[147],"AV1":[149],"anchor.":[150],"code":[152],"model":[154],"are":[158],"published":[159],"Github":[162],"website":[163],"[1].":[164]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}