{"id":"https://openalex.org/W4293519457","doi":"https://doi.org/10.1109/icme52920.2022.9859910","title":"Neural Network Based in-Loop Filter with Constrained Memory","display_name":"Neural Network Based in-Loop Filter with Constrained Memory","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4293519457","doi":"https://doi.org/10.1109/icme52920.2022.9859910"},"language":"en","primary_location":{"id":"doi:10.1109/icme52920.2022.9859910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859910","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100427863","display_name":"Liqiang Wang","orcid":"https://orcid.org/0000-0002-1265-4656"},"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":"Liqiang Wang","raw_affiliation_strings":["Tencent Media Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Media Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102847146","display_name":"Xiaozhong Xu","orcid":"https://orcid.org/0000-0002-1309-5470"},"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":"Xiaozhong Xu","raw_affiliation_strings":["Tencent Media Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Media Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"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 Media Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Media Lab","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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":0.691378116607666},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.608195960521698},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5346991419792175},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5280205607414246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4554457664489746},{"id":"https://openalex.org/keywords/composite-image-filter","display_name":"Composite image filter","score":0.4225912094116211},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33492225408554077},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.326829731464386},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.29645490646362305},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1960073709487915}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.691378116607666},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.608195960521698},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5346991419792175},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5280205607414246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4554457664489746},{"id":"https://openalex.org/C78087231","wikidata":"https://www.wikidata.org/wiki/Q5156759","display_name":"Composite image filter","level":3,"score":0.4225912094116211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33492225408554077},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.326829731464386},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29645490646362305},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1960073709487915},{"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/icme52920.2022.9859910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859910","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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":23,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1522301498","https://openalex.org/W2101700394","https://openalex.org/W2169161136","https://openalex.org/W2477177239","https://openalex.org/W2508457857","https://openalex.org/W2560533888","https://openalex.org/W2741137940","https://openalex.org/W2792186562","https://openalex.org/W2884585870","https://openalex.org/W2888285221","https://openalex.org/W2935381027","https://openalex.org/W2942307329","https://openalex.org/W2964157487","https://openalex.org/W2998156630","https://openalex.org/W3013522332","https://openalex.org/W3081342944","https://openalex.org/W3099887184","https://openalex.org/W3202918664","https://openalex.org/W4205541964","https://openalex.org/W6602211262","https://openalex.org/W6631190155","https://openalex.org/W6753412334"],"related_works":["https://openalex.org/W2386387936","https://openalex.org/W3107474891","https://openalex.org/W2383319832","https://openalex.org/W2367368021","https://openalex.org/W2113644136","https://openalex.org/W2802349271","https://openalex.org/W2953642700","https://openalex.org/W2400541731","https://openalex.org/W2796644724","https://openalex.org/W2147369198"],"abstract_inverted_index":{"In":[0,100],"this":[1],"paper,":[2],"neural":[3],"network":[4,81],"based":[5],"in-loop":[6],"filters":[7,41,104],"are":[8,39,43,63,105],"designed":[9,44],"to":[10,148],"explore":[11],"the":[12,17,27,29,53,56,60,67,70,80,87,101,108,124,127,143],"potential":[13],"performance":[14],"improvement":[15],"beyond":[16],"latest":[18,109],"video":[19],"coding":[20],"standard":[21],"Versatile":[22],"Video":[23],"Coding":[24],"(VVC).":[25],"Besides":[26],"performance,":[28],"model":[30,88],"memory":[31,49,129,145],"size":[32],"is":[33,77,89,121,139,146],"also":[34,64],"taken":[35],"into":[36,66,79,107],"consideration.":[37],"There":[38],"three":[40],"which":[42],"with":[45,52,126],"different":[46,84],"sizes":[47],"of":[48,112,116,134],"requirement.":[50],"Along":[51],"un-filtered":[54],"image,":[55],"prediction":[57],"image":[58,62],"and":[59,131],"partitioning":[61],"fed":[65,78],"network.":[68],"Additionally,":[69],"quantized":[71],"parameter":[72],"(QP)":[73],"or":[74,97],"slice":[75,98],"type":[76],"for":[82,123],"classifying":[83],"situations":[85],"when":[86],"shared":[90],"by":[91],"multiple":[92],"sequence":[93],"level":[94],"base":[95],"QPs":[96],"types.":[99],"experiments,":[102],"these":[103],"integrated":[106],"reference":[110],"software":[111],"VVC.":[113],"An":[114],"average":[115,133],"12.26%":[117],"YUV":[118,136],"BD-rate":[119,137],"saving":[120,138],"achieved":[122,140],"filter":[125],"largest":[128],"size,":[130],"an":[132],"10.20%":[135],"even":[141],"if":[142],"required":[144],"reduced":[147],"1/22.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}