{"id":"https://openalex.org/W7134824285","doi":"https://doi.org/10.48550/arxiv.2603.06766","title":"HiDE: Hierarchical Dictionary-Based Entropy Modeling for Learned Image Compression","display_name":"HiDE: Hierarchical Dictionary-Based Entropy Modeling for Learned Image Compression","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134824285","doi":"https://doi.org/10.48550/arxiv.2603.06766"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06766","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007976498","display_name":"Haoxuan Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Haoxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010707849","display_name":"Yuanyuan Xu","orcid":"https://orcid.org/0000-0001-7488-0758"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yuanyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128670356","display_name":"Kun Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128683904","display_name":"Yiming Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128689016","display_name":"Baoliu Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Baoliu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30496082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9348000288009644,"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":0.9348000288009644,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.012799999676644802,"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":0.010499999858438969,"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/prior-probability","display_name":"Prior probability","score":0.890999972820282},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7069000005722046},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5856000185012817},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5809000134468079},{"id":"https://openalex.org/keywords/conditional-entropy","display_name":"Conditional entropy","score":0.47049999237060547},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.4564000070095062},{"id":"https://openalex.org/keywords/prior-information","display_name":"Prior information","score":0.43230000138282776},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3871000111103058}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.890999972820282},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7069000005722046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6603999733924866},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5809000134468079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4708000123500824},{"id":"https://openalex.org/C101721835","wikidata":"https://www.wikidata.org/wiki/Q813908","display_name":"Conditional entropy","level":3,"score":0.47049999237060547},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4478999972343445},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.38589999079704285},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37389999628067017},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.36570000648498535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C106752470","wikidata":"https://www.wikidata.org/wiki/Q1364826","display_name":"Joint entropy","level":3,"score":0.2985000014305115},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C95546049","wikidata":"https://www.wikidata.org/wiki/Q1345207","display_name":"Entropy estimation","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2599000036716461},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06766","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06766","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06766","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.06766","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7096662521362305}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Learned":[0],"image":[1,115],"compression":[2,60],"(LIC)":[3],"has":[4],"achieved":[5],"remarkable":[6],"coding":[7],"efficiency,":[8],"where":[9],"entropy":[10,49,83],"modeling":[11,84,111],"plays":[12],"a":[13,70,92,107,140],"pivotal":[14],"role":[15],"in":[16,38,47,74],"minimizing":[17],"bitrate":[18],"through":[19],"informative":[20],"priors.":[21],"Existing":[22],"methods":[23],"predominantly":[24],"exploit":[25,152],"internal":[26],"contexts":[27,154],"within":[28,69],"the":[29,33,175],"input":[30],"image,":[31],"yet":[32],"rich":[34],"external":[35,55,67,119,137],"priors":[36,56,68,89,120],"embedded":[37],"large-scale":[39],"training":[40],"data":[41],"remain":[42],"largely":[43],"underutilized.":[44],"Recent":[45],"advances":[46],"dictionary-based":[48],"models":[50],"have":[51],"demonstrated":[52],"that":[53,163],"incorporating":[54],"can":[57],"substantially":[58],"enhance":[59],"performance.":[61],"However,":[62],"current":[63],"approaches":[64],"organize":[65],"heterogeneous":[66,153],"single-level":[71],"dictionary,":[72],"resulting":[73],"imbalanced":[75],"utilization":[76,135],"and":[77,124,133,168,178],"limited":[78],"representational":[79],"capacity.":[80],"Moreover,":[81,139],"effective":[82],"requires":[85],"not":[86],"only":[87],"expressive":[88],"but":[90],"also":[91],"parameter":[93,142],"estimation":[94],"network":[95],"capable":[96],"of":[97,136],"interpreting":[98],"them.":[99],"To":[100],"address":[101],"these":[102],"challenges,":[103],"we":[104],"propose":[105],"HiDE,":[106],"Hierarchical":[108],"Dictionary-based":[109],"Entropy":[110],"framework":[112],"for":[113,155],"learned":[114],"compression.":[116],"HiDE":[117,164],"decomposes":[118],"into":[121],"global":[122],"structural":[123],"local":[125],"detail":[126],"dictionaries":[127],"with":[128,144],"cascaded":[129],"retrieval,":[130],"enabling":[131],"structured":[132],"efficient":[134],"information.":[138],"context-aware":[141],"estimator":[143],"parallel":[145],"multi-receptive-field":[146],"design":[147],"is":[148],"introduced":[149],"to":[150],"adaptively":[151],"accurate":[156],"conditional":[157],"probability":[158],"estimation.":[159],"Experimental":[160],"results":[161],"show":[162],"achieves":[165],"18.5%,":[166],"21.99%,":[167],"24.01%":[169],"BD-rate":[170],"savings":[171],"over":[172],"VTM-12.1":[173],"on":[174],"Kodak,":[176],"CLIC,":[177],"Tecnick":[179],"datasets,":[180],"respectively.":[181]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}