{"id":"https://openalex.org/W4402916713","doi":"https://doi.org/10.1109/icip51287.2024.10648249","title":"Learned Compression of Encoding Distributions","display_name":"Learned Compression of Encoding Distributions","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402916713","doi":"https://doi.org/10.1109/icip51287.2024.10648249"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10648249","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648249","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 Image Processing (ICIP)","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/A5016388046","display_name":"Mateen Ulhaq","orcid":"https://orcid.org/0009-0002-1352-9969"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mateen Ulhaq","raw_affiliation_strings":["Simon Fraser University,School of Engineering Science,Burnaby,BC,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University,School of Engineering Science,Burnaby,BC,Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012187461","display_name":"Ivan V. Baji\u0107","orcid":"https://orcid.org/0000-0003-3154-5743"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ivan V. Baji\u0107","raw_affiliation_strings":["Simon Fraser University,School of Engineering Science,Burnaby,BC,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University,School of Engineering Science,Burnaby,BC,Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13525366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":null,"first_page":"3716","last_page":"3722"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.963100016117096,"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"}},"topics":[{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.963100016117096,"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"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9545999765396118,"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/encoding","display_name":"Encoding (memory)","score":0.7673808336257935},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6756237745285034},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.6276080012321472},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5064734220504761},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24673870205879211},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.06725093722343445}],"concepts":[{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.7673808336257935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6756237745285034},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.6276080012321472},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5064734220504761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24673870205879211},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.06725093722343445},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10648249","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10648249","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 Image Processing (ICIP)","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":22,"referenced_works":["https://openalex.org/W2118020555","https://openalex.org/W2552465432","https://openalex.org/W2769654144","https://openalex.org/W2785562966","https://openalex.org/W2963125010","https://openalex.org/W3034469748","https://openalex.org/W3097448661","https://openalex.org/W3120355627","https://openalex.org/W4205449766","https://openalex.org/W4312806968","https://openalex.org/W4317555471","https://openalex.org/W4386598402","https://openalex.org/W4387436812","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6690026940","https://openalex.org/W6734035190","https://openalex.org/W6748107402","https://openalex.org/W6754634825","https://openalex.org/W6763486759","https://openalex.org/W6774440223","https://openalex.org/W6798550133"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2612632602","https://openalex.org/W2321805087"],"abstract_inverted_index":{"The":[0,49],"entropy":[1],"bottleneck":[2],"introduced":[3],"by":[4,171],"Ball\u00e9":[5],"et":[6],"al.":[7],"[1]":[8],"is":[9,117,174],"a":[10,21,26,85,100,107,112,146],"common":[11],"component":[12],"used":[13,170],"in":[14,76,180],"many":[15],"learned":[16,32],"compression":[17],"models.":[18],"It":[19],"encodes":[20],"transformed":[22],"latent":[23,41,96,141],"representation":[24],"using":[25],"static":[27,50],"distribution":[28,38,51,92,98,110,116,133],"whose":[29],"parameters":[30],"are":[31],"during":[33],"training.":[34],"However,":[35],"the":[36,40,72,90,95,128,131,139,153,160,168,193],"actual":[37],"of":[39,62,150,177,182],"data":[42,97],"may":[43],"vary":[44],"wildly":[45],"across":[46],"different":[47],"inputs.":[48],"attempts":[52],"to":[53,93,137,159,187],"encompass":[54],"all":[55],"possible":[56],"input":[57],"distributions,":[58],"thus":[59],"fitting":[60],"none":[61],"them":[63],"particularly":[64],"well.":[65],"This":[66,115],"unfortunate":[67],"phenomenon,":[68],"sometimes":[69],"known":[70],"as":[71,122,192],"amortization":[73],"gap,":[74],"results":[75],"suboptimal":[77],"compression.":[78],"To":[79],"address":[80],"this":[81],"issue,":[82],"we":[83],"propose":[84],"method":[86,144,173],"that":[87],"dynamically":[88],"adapts":[89],"encoding":[91,109,132],"match":[94],"for":[99,111],"specific":[101],"input.":[102,114],"First,":[103],"our":[104,172],"model":[105],"estimates":[106],"better":[108],"given":[113],"then":[118],"compressed":[119],"and":[120,134],"transmitted":[121],"an":[123,175],"additional":[124],"side-information":[125,189],"bitstream.":[126],"Finally,":[127],"decoder":[129],"reconstructs":[130],"uses":[135],"it":[136],"decompress":[138],"corresponding":[140],"data.":[142],"Our":[143],"achieves":[145],"Bj\u00f8ntegaard-Delta":[147],"(BD)-rate":[148],"gain":[149],"-7.10%":[151],"on":[152],"Kodak":[154],"test":[155],"dataset":[156],"when":[157],"applied":[158],"standard":[161],"fully-factorized":[162],"architecture.":[163],"Furthermore,":[164],"considering":[165],"computational":[166],"complexity,":[167],"transform":[169],"order":[176],"magnitude":[178],"cheaper":[179],"terms":[181],"Multiply-Accumulate":[183],"(MAC)":[184],"operations":[185],"compared":[186],"related":[188],"methods":[190],"such":[191],"scale":[194],"hyperprior.":[195]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
