{"id":"https://openalex.org/W3035750301","doi":"https://doi.org/10.1109/icip40778.2020.9191193","title":"Interpreting CNN For Low Complexity Learned Sub-Pixel Motion Compensation In Video Coding","display_name":"Interpreting CNN For Low Complexity Learned Sub-Pixel Motion Compensation In Video Coding","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3035750301","doi":"https://doi.org/10.1109/icip40778.2020.9191193","mag":"3035750301"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191193","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":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2006.06392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Luka Murn","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Luka Murn","raw_affiliation_strings":["BBC Research and Development, London, UK"],"affiliations":[{"raw_affiliation_string":"BBC Research and Development, London, UK","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Saverio Blasi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saverio Blasi","raw_affiliation_strings":["BBC Research and Development, London, UK"],"affiliations":[{"raw_affiliation_string":"BBC Research and Development, London, UK","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Alan F. Smeaton","orcid":null},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Alan F. Smeaton","raw_affiliation_strings":["Dublin City University, Dublin, Ireland"],"affiliations":[{"raw_affiliation_string":"Dublin City University, Dublin, Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Noel E. O'Connor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Noel E. O'Connor","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Marta Mrak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marta Mrak","raw_affiliation_strings":["BBC Research and Development, London, UK"],"affiliations":[{"raw_affiliation_string":"BBC Research and Development, London, UK","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8832,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76242396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"798","last_page":"802"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.6571000218391418},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6500999927520752},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5665000081062317},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5575000047683716},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4178999960422516},{"id":"https://openalex.org/keywords/coding-tree-unit","display_name":"Coding tree unit","score":0.40779998898506165},{"id":"https://openalex.org/keywords/motion-interpolation","display_name":"Motion interpolation","score":0.40720000863075256},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.366100013256073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7264000177383423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6985999941825867},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.6571000218391418},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6500999927520752},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5893999934196472},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5665000081062317},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5575000047683716},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C190750250","wikidata":"https://www.wikidata.org/wiki/Q13533439","display_name":"Coding tree unit","level":3,"score":0.40779998898506165},{"id":"https://openalex.org/C72560505","wikidata":"https://www.wikidata.org/wiki/Q204510","display_name":"Motion interpolation","level":5,"score":0.40720000863075256},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30809998512268066},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C174493125","wikidata":"https://www.wikidata.org/wiki/Q1073461","display_name":"Quarter-pixel motion","level":3,"score":0.28209999203681946},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.2815000116825104},{"id":"https://openalex.org/C175732694","wikidata":"https://www.wikidata.org/wiki/Q1128713","display_name":"Context-adaptive binary arithmetic coding","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C117090137","wikidata":"https://www.wikidata.org/wiki/Q7927977","display_name":"Video post-processing","level":5,"score":0.26809999346733093},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip40778.2020.9191193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191193","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"},{"id":"pmh:oai:arXiv.org:2006.06392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.06392","pdf_url":"https://arxiv.org/pdf/2006.06392","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:2006.06392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.06392","pdf_url":"https://arxiv.org/pdf/2006.06392","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":17,"referenced_works":["https://openalex.org/W2005003004","https://openalex.org/W2101700394","https://openalex.org/W2146395539","https://openalex.org/W2508457857","https://openalex.org/W2605341393","https://openalex.org/W2610377192","https://openalex.org/W2791933231","https://openalex.org/W2910705748","https://openalex.org/W2935381027","https://openalex.org/W2936017994","https://openalex.org/W2945937811","https://openalex.org/W2967151712","https://openalex.org/W2971165182","https://openalex.org/W2982955589","https://openalex.org/W6639309558","https://openalex.org/W6725165783","https://openalex.org/W6789352253"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"shown":[3],"great":[4],"potential":[5,29],"in":[6,23,84],"image":[7],"and":[8],"video":[9],"compression":[10],"tasks.":[11],"However,":[12],"it":[13],"brings":[14],"bit":[15],"savings":[16],"at":[17],"the":[18,47,62,72,77,80,85,104,108,118],"cost":[19],"of":[20,49,110,120],"significant":[21],"increases":[22],"coding":[24],"complexity,":[25],"which":[26,45],"limits":[27],"its":[28],"for":[30,53,97],"implementation":[31],"within":[32],"practical":[33],"applications.":[34],"In":[35],"this":[36],"paper,":[37],"a":[38],"novel":[39],"neural":[40,122],"network-based":[41],"tool":[42],"is":[43,82,100,113],"presented":[44],"improves":[46],"interpolation":[48,73,112],"reference":[50],"samples":[51],"needed":[52],"fractional":[54],"precision":[55],"motion":[56],"compensation.":[57],"Contrary":[58],"to":[59,93,117],"previous":[60],"efforts,":[61],"proposed":[63],"approach":[64,81],"focuses":[65],"on":[66],"complexity":[67,109],"reduction":[68],"achieved":[69,101],"by":[70,76],"interpreting":[71],"filters":[74],"learned":[75,111],"networks.":[78],"When":[79],"implemented":[83],"Versatile":[86],"Video":[87],"Coding":[88],"(VVC)":[89],"test":[90],"model,":[91],"up":[92],"4.5%":[94],"BD-rate":[95],"saving":[96],"individual":[98],"sequences":[99],"compared":[102,116],"with":[103],"baseline":[105],"VVC,":[106],"while":[107],"significantly":[114],"reduced":[115],"application":[119],"full":[121],"network.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-06-19T00:00:00"}