{"id":"https://openalex.org/W4412610730","doi":"https://doi.org/10.1109/hpcc64274.2024.00015","title":"Lightweight Autoencoder with Hierarchical Priors for Learned Image Compression","display_name":"Lightweight Autoencoder with Hierarchical Priors for Learned Image Compression","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4412610730","doi":"https://doi.org/10.1109/hpcc64274.2024.00015"},"language":"en","primary_location":{"id":"doi:10.1109/hpcc64274.2024.00015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00015","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 High Performance Computing and Communications (HPCC)","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/A5056068917","display_name":"Junwei Zhou","orcid":"https://orcid.org/0000-0002-6094-1203"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junwei Zhou","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000980235","display_name":"Qiao Huang","orcid":"https://orcid.org/0000-0002-9044-2464"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Huang","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100698920","display_name":"Xiang Tian","orcid":"https://orcid.org/0000-0001-5486-8073"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Xiang","raw_affiliation_strings":["Hubei University of Technology,Detroit Green Technology Institute,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei University of Technology,Detroit Green Technology Institute,Wuhan,China","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058737960","display_name":"Lei Zhou","orcid":"https://orcid.org/0000-0003-0860-0724"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhou","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108054841","display_name":"Yanchao Yang","orcid":"https://orcid.org/0000-0002-2447-7917"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanchao Yang","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016677170","display_name":"Jianwen Xiang","orcid":"https://orcid.org/0000-0001-8440-4181"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwen Xiang","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.39114506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.972000002861023,"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":0.972000002861023,"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/autoencoder","display_name":"Autoencoder","score":0.911259651184082},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7992738485336304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6425509452819824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.614152193069458},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5486375689506531},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5439110398292542},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.5434011816978455},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4196482002735138},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.388333261013031},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2938673496246338},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.20815613865852356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19809883832931519},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.05368497967720032}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.911259651184082},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7992738485336304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6425509452819824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.614152193069458},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5486375689506531},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5439110398292542},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.5434011816978455},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4196482002735138},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.388333261013031},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2938673496246338},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.20815613865852356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19809883832931519},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.05368497967720032},{"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/hpcc64274.2024.00015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00015","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 High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2423557781","https://openalex.org/W2785562966","https://openalex.org/W2962785568","https://openalex.org/W2962891349","https://openalex.org/W3015735225","https://openalex.org/W3034251466","https://openalex.org/W3034368386","https://openalex.org/W3034469748","https://openalex.org/W3092916389","https://openalex.org/W3096281486","https://openalex.org/W3112858938","https://openalex.org/W3131427579","https://openalex.org/W3134748538","https://openalex.org/W3162366763","https://openalex.org/W3168997536","https://openalex.org/W3170851022","https://openalex.org/W3172265425","https://openalex.org/W3172982968","https://openalex.org/W3173563913","https://openalex.org/W3175457126","https://openalex.org/W3176350758","https://openalex.org/W3181161645","https://openalex.org/W3206996732","https://openalex.org/W4230291482","https://openalex.org/W4292256660","https://openalex.org/W4312806968","https://openalex.org/W4361019821","https://openalex.org/W4361020036","https://openalex.org/W4376112629","https://openalex.org/W4385805159","https://openalex.org/W6737664043","https://openalex.org/W6754634825","https://openalex.org/W6796815506","https://openalex.org/W6797854001","https://openalex.org/W6843239693","https://openalex.org/W6849793491"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W3153124080"],"abstract_inverted_index":{"Image":[0],"compression":[1,19],"has":[2],"become":[3],"an":[4],"important":[5],"task":[6],"for":[7,16],"reducing":[8],"storage":[9],"and":[10,30,42,76,84,107,146],"transmission":[11],"costs.":[12],"However,":[13],"recent":[14],"models":[15],"learned":[17],"image":[18],"have":[20],"been":[21],"developed":[22],"to":[23,32],"increase":[24],"the":[25,47,72,89,94,101,108,116,119,131,138,142],"network\u2019s":[26],"number":[27],"of":[28,88,127],"layers":[29],"channels":[31],"achieve":[33],"better":[34],"visual":[35],"effects.":[36],"This":[37],"resulted":[38],"in":[39,123],"higher":[40],"computing":[41],"memory":[43],"resources,":[44],"making":[45],"deploying":[46],"model":[48,96,121,135],"on":[49,80,144],"compute-constrained":[50],"platforms":[51],"such":[52],"as":[53,141],"wireless":[54],"devices":[55],"impractical.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"propose":[61],"a":[62,98,124],"lightweight":[63,69],"autoencoder":[64,70],"with":[65],"hierarchical":[66],"priors.":[67],"The":[68],"reduces":[71],"model\u2019s":[73],"parameter":[74],"size":[75],"calculation":[77,109],"amount":[78,110],"based":[79],"ensuring":[81],"high":[82],"fidelity":[83],"low":[85],"bit":[86],"rates":[87],"image.":[90],"Simulation":[91],"results":[92,122],"indicate":[93],"proposed":[95,120],"yields":[97],"smaller":[99],"size:":[100],"parameters":[102],"are":[103],"reduced":[104,112],"by":[105,113],"81.66%,":[106],"is":[111],"94.7%":[114],"over":[115],"benchmark.":[117],"Besides,":[118],"speed":[125],"improvement":[126],"200":[128],"times.":[129],"At":[130],"same":[132,139],"time,":[133],"our":[134],"achieves":[136],"nearly":[137],"performance":[140],"baseline":[143],"MS-SSIM":[145],"LPIPS":[147],"distortion":[148],"metrics.":[149]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}