{"id":"https://openalex.org/W4400232872","doi":"https://doi.org/10.1109/iscas58744.2024.10558613","title":"VQNeRV: Vector Quantization Neural Representation for Video Compression","display_name":"VQNeRV: Vector Quantization Neural Representation for Video Compression","publication_year":2024,"publication_date":"2024-05-19","ids":{"openalex":"https://openalex.org/W4400232872","doi":"https://doi.org/10.1109/iscas58744.2024.10558613"},"language":"en","primary_location":{"id":"doi:10.1109/iscas58744.2024.10558613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas58744.2024.10558613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5101498134","display_name":"Gai Zhang","orcid":"https://orcid.org/0000-0003-0418-0689"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gai Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101498637","display_name":"Lv Tang","orcid":"https://orcid.org/0000-0001-7359-1057"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lv Tang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055937409","display_name":"Xinfeng Zhang","orcid":"https://orcid.org/0000-0002-7517-3868"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinfeng Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.0517,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81380726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9927999973297119,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9927999973297119,"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":0.9751999974250793,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9749000072479248,"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/vector-quantization","display_name":"Vector quantization","score":0.7844735383987427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6428558230400085},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6127336025238037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5264376401901245},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.5218804478645325},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49805521965026855},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.49306318163871765},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45736536383628845}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.7844735383987427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6428558230400085},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6127336025238037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5264376401901245},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.5218804478645325},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49805521965026855},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.49306318163871765},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45736536383628845},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas58744.2024.10558613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas58744.2024.10558613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2101700394","https://openalex.org/W2140199336","https://openalex.org/W2146395539","https://openalex.org/W2612846844","https://openalex.org/W2791933231","https://openalex.org/W2969260367","https://openalex.org/W3018065762","https://openalex.org/W3163735346","https://openalex.org/W3173272744","https://openalex.org/W3180355996","https://openalex.org/W3202918664","https://openalex.org/W3203234039","https://openalex.org/W3213174511","https://openalex.org/W4285483958","https://openalex.org/W4312493191","https://openalex.org/W4312547480","https://openalex.org/W4313023779","https://openalex.org/W4386065618","https://openalex.org/W4390871851","https://openalex.org/W4390872754","https://openalex.org/W6631190155","https://openalex.org/W6675207249","https://openalex.org/W6799489178","https://openalex.org/W6802036239","https://openalex.org/W6803493554"],"related_works":["https://openalex.org/W2100968651","https://openalex.org/W4243803532","https://openalex.org/W2142248489","https://openalex.org/W2352648934","https://openalex.org/W4230688072","https://openalex.org/W1915693853","https://openalex.org/W1530525041","https://openalex.org/W2378212145","https://openalex.org/W2798892016","https://openalex.org/W2202992072"],"abstract_inverted_index":{"The":[0],"application":[1],"of":[2,14,39,56],"Implicit":[3],"Neural":[4,83],"Representations":[5],"(INR)":[6],"for":[7,66,88],"video":[8,89,111],"compression":[9],"represents":[10],"an":[11,147],"evolving":[12],"area":[13],"research.":[15],"Despite":[16],"its":[17],"potential,":[18],"conventional":[19],"CNN-based":[20,102],"INR":[21,103,148],"methods":[22],"often":[23],"encounter":[24],"difficulties":[25],"in":[26,41,94],"modeling":[27],"complex":[28],"spatiotemporal":[29,57,124,155],"scenes.":[30],"This":[31],"is":[32,119],"primarily":[33],"due":[34],"to":[35,49,62,71,108,122,174],"the":[36,54,110,127,135,151,159,175],"inherent":[37],"limitations":[38],"CNNs":[40],"extracting":[42],"intricate":[43],"information,":[44,157],"particularly":[45],"when":[46],"it":[47],"comes":[48],"capturing":[50],"temporal":[51],"dynamics.":[52],"Consequently,":[53],"integration":[55],"contextual":[58,156],"information":[59],"becomes":[60],"imperative":[61],"enhance":[63],"INR's":[64],"capacity":[65],"scene":[67],"modeling.":[68],"In":[69],"response":[70],"these":[72],"challenges,":[73],"this":[74],"paper":[75],"introduces":[76],"a":[77,101,114,142,168],"novel":[78],"approach,":[79],"termed":[80],"Vector":[81,115],"Quantization":[82,116],"Representation":[84],"(VQNeRV),":[85],"specifically":[86],"designed":[87],"compression.":[90],"Our":[91],"methodology":[92],"unfolds":[93],"three":[95],"distinct":[96],"stages:":[97],"Firstly,":[98],"we":[99],"establish":[100],"equipped":[104],"with":[105,134],"spatial":[106,136],"embeddings":[107,137],"model":[109],"content.":[112],"Secondly,":[113],"(VQ)":[117],"encoder":[118],"then":[120],"utilized":[121],"distill":[123],"features":[125,130,153],"from":[126],"video.":[128,160],"These":[129],"are":[131],"subsequently":[132],"amalgamated":[133],"through":[138],"cross-attention":[139],"mechanisms,":[140],"facilitating":[141],"comprehensive":[143],"feature":[144],"fusion.":[145],"Finally,":[146],"decoder,":[149],"leveraging":[150],"combined":[152],"embodying":[154],"reconstructs":[158],"Experimental":[161],"results":[162],"demonstrate":[163],"that":[164],"our":[165],"method":[166],"shows":[167],"much":[169],"better":[170],"rate-distortion":[171],"performance":[172],"compared":[173],"VVC.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}