{"id":"https://openalex.org/W4406861417","doi":"https://doi.org/10.1109/vcip63160.2024.10849907","title":"PET-NeRV: Bridging Generalized Video Codec and Content-Specific Neural Representation","display_name":"PET-NeRV: Bridging Generalized Video Codec and Content-Specific Neural Representation","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4406861417","doi":"https://doi.org/10.1109/vcip63160.2024.10849907"},"language":"en","primary_location":{"id":"doi:10.1109/vcip63160.2024.10849907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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/A5100348625","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-6959-3233"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Li","raw_affiliation_strings":["Zhejiang University,HangZhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,HangZhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106403416","display_name":"Lu Yu","orcid":"https://orcid.org/0000-0002-0550-7754"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Yu","raw_affiliation_strings":["Zhejiang University,HangZhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,HangZhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018811297","display_name":"Yiyi Liao","orcid":"https://orcid.org/0000-0001-6662-3022"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyi Liao","raw_affiliation_strings":["Zhejiang University,HangZhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,HangZhou,China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100348625"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4360114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9445000290870667,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9132000207901001,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/codec","display_name":"Codec","score":0.7829964756965637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6908233165740967},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.548875629901886},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4461810290813446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36281687021255493},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3233415484428406},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.12613871693611145},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09126129746437073}],"concepts":[{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.7829964756965637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6908233165740967},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.548875629901886},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4461810290813446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36281687021255493},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3233415484428406},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.12613871693611145},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09126129746437073},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/vcip63160.2024.10849907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2101700394","https://openalex.org/W2909370231","https://openalex.org/W2963189365","https://openalex.org/W3031546776","https://openalex.org/W3110286842","https://openalex.org/W3215581463","https://openalex.org/W3216456501","https://openalex.org/W4285483958","https://openalex.org/W4287756134","https://openalex.org/W4289387907","https://openalex.org/W4312493191","https://openalex.org/W4390871708","https://openalex.org/W4391952654","https://openalex.org/W6680751073","https://openalex.org/W6681628524","https://openalex.org/W6759579507","https://openalex.org/W6763486759","https://openalex.org/W6770102382","https://openalex.org/W6785343060","https://openalex.org/W6794643271","https://openalex.org/W6796581206","https://openalex.org/W6802036239","https://openalex.org/W6803493554","https://openalex.org/W6804186294","https://openalex.org/W6810353303","https://openalex.org/W6810601475","https://openalex.org/W6811329210","https://openalex.org/W6839976848","https://openalex.org/W6845810032","https://openalex.org/W6846281300","https://openalex.org/W6847509130","https://openalex.org/W6848483209","https://openalex.org/W6850500859","https://openalex.org/W6851057193","https://openalex.org/W6853577868","https://openalex.org/W6854138689"],"related_works":["https://openalex.org/W4388870064","https://openalex.org/W2210139803","https://openalex.org/W4235186151","https://openalex.org/W2054685365","https://openalex.org/W2056057048","https://openalex.org/W2667588871","https://openalex.org/W2272354214","https://openalex.org/W2964213236","https://openalex.org/W2084768720","https://openalex.org/W2163719598"],"abstract_inverted_index":{"Generalized":[0],"models":[1],"dominate":[2],"neural":[3,19],"video":[4,10,39,72,75],"compression":[5,23,100,146],"methods":[6],"to":[7,33,54,69,124,141,149],"compress":[8],"arbitrary":[9],"with":[11,21,88],"the":[12,35,57,99,114,150],"same":[13],"model.":[14],"However,":[15],"obtaining":[16],"a":[17,48,78,104,142],"universal":[18],"codec":[20],"high":[22],"efficiency":[24,101,147],"on":[25],"all":[26],"videos":[27],"is":[28],"challenging.":[29],"Existing":[30],"work":[31],"attempts":[32],"adapt":[34],"decoder-side":[36],"model":[37],"per":[38,74],"content":[40,76],"through":[41],"full":[42],"parameter":[43],"tuning,":[44],"but":[45],"this":[46,65],"requires":[47],"large":[49],"Group":[50],"of":[51,59,118],"Pictures":[52],"(GOP)":[53],"compensate":[55],"for":[56,97,108],"cost":[58],"transmitting":[60],"updated":[61],"parameters.":[62],"To":[63,112],"tackle":[64],"challenge,":[66],"we":[67,121],"propose":[68],"tune":[70],"generalized":[71],"codecs":[73],"in":[77,145],"parameter-efficient":[79],"manner.":[80],"The":[81],"per-content":[82],"tuned":[83],"parameters":[84],"are":[85],"further":[86],"compressed":[87],"entropy":[89],"coding":[90],"using":[91],"adaptive":[92],"distribution":[93],"estimations.":[94],"This":[95],"allows":[96],"enhancing":[98],"while":[102],"maintaining":[103],"normal":[105],"GOP":[106],"size":[107],"random":[109],"access":[110],"capabilities.":[111],"validate":[113],"generality":[115],"and":[116,130],"validity":[117],"our":[119],"approach,":[120],"apply":[122],"it":[123],"two":[125],"representative":[126],"methods:":[127],"CNN-based,":[128],"DCVC-HEM,":[129],"Transformer-based,":[131],"VCT.":[132],"Our":[133],"results":[134],"demonstrate":[135],"that":[136],"introducing":[137],"content-specific":[138],"representation":[139],"leads":[140],"notable":[143],"improvement":[144],"compared":[148],"original":[151],"methods.":[152]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
