{"id":"https://openalex.org/W3091740610","doi":"https://doi.org/10.1109/icip40778.2020.9191106","title":"Residual Guided Deblocking With Deep Learning","display_name":"Residual Guided Deblocking With Deep Learning","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3091740610","doi":"https://doi.org/10.1109/icip40778.2020.9191106","mag":"3091740610"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5101935663","display_name":"Wei Jia","orcid":"https://orcid.org/0000-0003-0053-6959"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Jia","raw_affiliation_strings":["University of Missouri, Kansas City"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361230","display_name":"Li Li","orcid":"https://orcid.org/0000-0002-7163-6263"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["University of Missouri, Kansas City"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380624","display_name":"Zhu Li","orcid":"https://orcid.org/0000-0002-7369-2744"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhu Li","raw_affiliation_strings":["University of Missouri, Kansas City"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368873","display_name":"Xiang Zhang","orcid":"https://orcid.org/0000-0002-6002-1503"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["University of Missouri, Kansas City"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Missouri, Kansas City","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100449791","display_name":"Shan Liu","orcid":"https://orcid.org/0000-0002-1442-1207"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Liu","raw_affiliation_strings":["Tencent, America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, America","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3109","last_page":"3113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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":0.8010234236717224},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.7718394994735718},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7680267691612244},{"id":"https://openalex.org/keywords/residual-frame","display_name":"Residual frame","score":0.7465401887893677},{"id":"https://openalex.org/keywords/deblocking-filter","display_name":"Deblocking filter","score":0.7318022847175598},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6000515222549438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5930254459381104},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5163577795028687},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4623926877975464},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4168764054775238},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39138346910476685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3567216992378235},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.3222266137599945},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2868884801864624},{"id":"https://openalex.org/keywords/reference-frame","display_name":"Reference frame","score":0.2605017125606537},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.24754291772842407},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.17435699701309204},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09404075145721436},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0789136290550232},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07820221781730652}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8010234236717224},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.7718394994735718},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7680267691612244},{"id":"https://openalex.org/C204641915","wikidata":"https://www.wikidata.org/wiki/Q7315509","display_name":"Residual frame","level":4,"score":0.7465401887893677},{"id":"https://openalex.org/C143184774","wikidata":"https://www.wikidata.org/wiki/Q3020846","display_name":"Deblocking filter","level":2,"score":0.7318022847175598},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6000515222549438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5930254459381104},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5163577795028687},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4623926877975464},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4168764054775238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39138346910476685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3567216992378235},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3222266137599945},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2868884801864624},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.2605017125606537},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.24754291772842407},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.17435699701309204},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09404075145721436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0789136290550232},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07820221781730652},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W597288515","https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1901129140","https://openalex.org/W2096076665","https://openalex.org/W2100495367","https://openalex.org/W2106692341","https://openalex.org/W2123113293","https://openalex.org/W2140199336","https://openalex.org/W2146395539","https://openalex.org/W2194775991","https://openalex.org/W2293078015","https://openalex.org/W2510648513","https://openalex.org/W2560512785","https://openalex.org/W2741137940","https://openalex.org/W2757828535","https://openalex.org/W2799309438","https://openalex.org/W2895518292","https://openalex.org/W2953046278","https://openalex.org/W2964121744","https://openalex.org/W3102974666","https://openalex.org/W3104772632","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6730998768","https://openalex.org/W6744386365"],"related_works":["https://openalex.org/W1541069754","https://openalex.org/W2912360874","https://openalex.org/W2618155942","https://openalex.org/W28590286","https://openalex.org/W2370786670","https://openalex.org/W49893467","https://openalex.org/W4206603417","https://openalex.org/W3156895831","https://openalex.org/W4372278960","https://openalex.org/W3091740610"],"abstract_inverted_index":{"The":[0,172],"block-based":[1],"coding":[2,7,33,61],"structure":[3,126],"in":[4,40,47,99,106,131,164,201],"hybrid":[5],"video":[6,170,206],"framework":[8],"inevitably":[9],"introduces":[10],"compression":[11],"artifacts":[12],"such":[13,109],"as":[14,76],"blocking,":[15],"ringing":[16],"etc.":[17],"Recently,":[18],"neural":[19,44],"network":[20,75,125,135],"based":[21],"loop":[22],"filters":[23],"are":[24],"proposed":[25,133,178],"to":[26,58,63,80,117,136,182,187],"enhance":[27],"the":[28,32,41,60,68,74,81,86,124,132,149,156,161,165,190,202],"reconstructed":[29,82,205],"frame.":[30,83],"But":[31],"information":[34,92,140],"has":[35,127],"not":[36],"been":[37,128],"full":[38,65],"utilized":[39],"design":[42],"of":[43,151,204],"networks.":[45],"Therefore,":[46],"this":[48,154],"paper,":[49],"we":[50],"propose":[51],"a":[52,77,107],"Residual-Reconstruction-based":[53],"Convolutional":[54],"Neural":[55],"Network":[56],"(RRCNN)":[57],"improve":[59],"efficiency":[62],"its":[64],"extent,":[66],"where":[67],"residual":[69,87,162,195],"frame":[70],"is":[71,155],"fed":[72],"into":[73],"supplementary":[78],"input":[79],"In":[84,122],"essence,":[85],"signal":[88,163,196],"can":[89,97,114],"provide":[90],"effective":[91],"about":[93],"block":[94],"partitions":[95],"and":[96,103,189],"help":[98],"recognizing":[100],"smooth,":[101],"edge":[102],"texture":[104,120],"regions":[105],"picture,":[108],"that":[110,159,176],"more":[111],"adaptive":[112],"parameters":[113],"be":[115],"trained":[116],"handle":[118],"different":[119],"characteristics.":[121],"addition,":[123],"carefully":[129],"designed":[130],"dual-input":[134],"learn":[137],"useful":[138],"context":[139],"from":[141],"two":[142],"signals":[143],"with":[144],"their":[145],"distinct":[146],"features.":[147],"To":[148],"best":[150],"our":[152,177],"knowledge,":[153],"first":[157],"work":[158],"employs":[160],"CNN-based":[166,192],"in-loop":[167],"filter":[168],"for":[169],"coding.":[171],"experimental":[173],"results":[174],"show":[175],"RRCNN":[179],"approach":[180],"leads":[181],"significant":[183],"BD-rate":[184],"savings":[185],"compared":[186],"HEVC":[188],"state-of-the-art":[191],"schemes,":[193],"indicating":[194],"plays":[197],"an":[198],"important":[199],"role":[200],"enhancement":[203],"frames.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
