{"id":"https://openalex.org/W4408861750","doi":"https://doi.org/10.1109/icce63647.2025.10929842","title":"Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression","display_name":"Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression","publication_year":2025,"publication_date":"2025-01-11","ids":{"openalex":"https://openalex.org/W4408861750","doi":"https://doi.org/10.1109/icce63647.2025.10929842"},"language":"en","primary_location":{"id":"doi:10.1109/icce63647.2025.10929842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10929842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","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/A5003035267","display_name":"Takahiro Shindo","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takahiro Shindo","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053367139","display_name":"Taiju Watanabe","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiju Watanabe","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102674043","display_name":"Yui Tatsumi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yui Tatsumi","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088389427","display_name":"Hiroshi Watanabe","orcid":"https://orcid.org/0000-0002-6742-1913"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Watanabe","raw_affiliation_strings":["Waseda University,Tokyo,Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003035267"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":9.9395,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97515553,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"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/T10320","display_name":"Neural Networks and Applications","score":0.9821000099182129,"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/T10320","display_name":"Neural Networks and Applications","score":0.9821000099182129,"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":0.972599983215332,"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":0.9584000110626221,"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/delta","display_name":"Delta","score":0.8647390604019165},{"id":"https://openalex.org/keywords/dirac-delta-function","display_name":"Dirac delta function","score":0.5246946215629578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.476043701171875},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44422051310539246},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.21629446744918823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1972614824771881},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.06256431341171265},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.05794942378997803}],"concepts":[{"id":"https://openalex.org/C5072461","wikidata":"https://www.wikidata.org/wiki/Q49506","display_name":"Delta","level":2,"score":0.8647390604019165},{"id":"https://openalex.org/C54486999","wikidata":"https://www.wikidata.org/wiki/Q209675","display_name":"Dirac delta function","level":2,"score":0.5246946215629578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.476043701171875},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44422051310539246},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.21629446744918823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1972614824771881},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.06256431341171265},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05794942378997803},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce63647.2025.10929842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10929842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5942591708","display_name":null,"funder_award_id":"JPJ012368C05101","funder_id":"https://openalex.org/F4320335839","funder_display_name":"National Institute of Information and Communications Technology"}],"funders":[{"id":"https://openalex.org/F4320335839","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W832984975","https://openalex.org/W1861492603","https://openalex.org/W2140196014","https://openalex.org/W2552465432","https://openalex.org/W2785562966","https://openalex.org/W2962802655","https://openalex.org/W2963150697","https://openalex.org/W2963661664","https://openalex.org/W3034469748","https://openalex.org/W3091266734","https://openalex.org/W3160673571","https://openalex.org/W3169876831","https://openalex.org/W3171673455","https://openalex.org/W3175457126","https://openalex.org/W4226355936","https://openalex.org/W4284691924","https://openalex.org/W4308233870","https://openalex.org/W4312806968","https://openalex.org/W4317555243","https://openalex.org/W4362496227","https://openalex.org/W4372260482","https://openalex.org/W4386075611","https://openalex.org/W4387245321","https://openalex.org/W4388187175","https://openalex.org/W4388726361","https://openalex.org/W4389474451","https://openalex.org/W4390874575","https://openalex.org/W4392931027","https://openalex.org/W4392980423","https://openalex.org/W4402915458","https://openalex.org/W4404295444","https://openalex.org/W6754634825","https://openalex.org/W6803627629","https://openalex.org/W6867140688","https://openalex.org/W6950310954"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4221046490","https://openalex.org/W4297616267","https://openalex.org/W2502651140","https://openalex.org/W3195406774","https://openalex.org/W4297615481","https://openalex.org/W4297616317","https://openalex.org/W3111070561"],"abstract_inverted_index":{"Image":[0,79],"Coding":[1],"for":[2,27,41,87,122,126,186,224],"Machines":[3],"(ICM)":[4],"is":[5,16,120,138],"becoming":[6],"more":[7],"important":[8],"as":[9,173],"research":[10,19],"in":[11,140,234],"computer":[12],"vision":[13],"progresses.":[14],"ICM":[15,63,141,232],"a":[17,115,161,166,174],"vital":[18],"field":[20],"that":[21,108,149],"pursues":[22],"the":[23,89,95,109,144,170,180,190,208,213,217,221],"use":[24],"of":[25,91,97,111,146,176,182],"images":[26,124],"image":[28,33,54,73,147,183,235],"recognition":[29,42],"models,":[30],"facilitating":[31],"efficient":[32],"transmission":[34],"and":[35,38,59,94,216],"storage.":[36],"Demand":[37],"required":[39],"performance":[40,237],"models":[43],"are":[44],"rapidly":[45],"growing":[46],"within":[47],"consumers.":[48],"To":[49,153],"meet":[50],"these":[51],"needs,":[52],"exchanging":[53],"data":[55],"between":[56,207],"consumer":[57],"devices":[58],"cloud":[60],"AI":[61],"using":[62,193],"technology":[64],"could":[65],"be":[66],"one":[67,218],"possible":[68],"solution.":[69],"In":[70],"ICM,":[71],"various":[72],"compression":[74,236],"methods":[75,106,233],"have":[76],"adopted":[77],"Learned":[78],"Compression":[80],"(LIC).":[81],"LIC":[82,105],"includes":[83],"an":[84,131,194],"entropy":[85,132,181,195,209],"model":[86,99,133,196,210],"estimating":[88],"bitrate":[90],"latent":[92,112,177,226],"features,":[93],"design":[96],"this":[98],"significantly":[100],"affects":[101],"its":[102],"performance.":[103],"Typically,":[104],"assume":[107],"distribution":[110,137,163,172,175,215,223],"features":[113,178],"follows":[114],"normal":[116,136,199,222],"distribution.":[117],"This":[118],"assumption":[119],"effective":[121],"compressing":[123],"intended":[125],"human":[127],"vision.":[128],"However,":[129],"employing":[130],"based":[134,164,197,211,219],"on":[135,165,198,212,220],"inefficient":[139],"due":[142],"to":[143,202],"limitation":[145],"parts":[148],"require":[150],"precise":[151],"decoding.":[152],"address":[154],"this,":[155],"we":[156],"propose":[157],"Delta-ICM,":[158],"which":[159],"uses":[160],"probability":[162],"delta":[167,171,214],"function.":[168],"Assuming":[169],"reduces":[179],"portions":[184,192],"unnecessary":[185],"machines.":[187,240],"We":[188],"compress":[189],"remaining":[191],"distribution,":[200],"similar":[201],"existing":[203,231],"methods.":[204],"Delta-ICM":[205],"selects":[206],"each":[225],"feature.":[227],"Our":[228],"method":[229],"outperforms":[230],"aimed":[238],"at":[239]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}