{"id":"https://openalex.org/W4415539285","doi":"https://doi.org/10.1145/3746027.3755599","title":"Unicorn: Unified Neural Image Compression with One Number Reconstruction","display_name":"Unicorn: Unified Neural Image Compression with One Number Reconstruction","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539285","doi":"https://doi.org/10.1145/3746027.3755599"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5089222298","display_name":"Qi Zheng","orcid":"https://orcid.org/0000-0002-9340-6709"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Zheng","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9340-6709","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haozhi Wang","orcid":"https://orcid.org/0009-0009-2988-5440"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haozhi Wang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-2988-5440","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005972548","display_name":"Z. Q. Liu","orcid":"https://orcid.org/0009-0005-2182-3123"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihao Liu","raw_affiliation_strings":["Alibaba Group, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-2182-3123","affiliations":[{"raw_affiliation_string":"Alibaba Group, Shanghai, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440966","display_name":"Jiaming Liu","orcid":"https://orcid.org/0000-0001-9629-9788"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaming Liu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9629-9788","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044357493","display_name":"Zhijian Hao","orcid":"https://orcid.org/0000-0002-7892-5973"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijian Hao","raw_affiliation_strings":["Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-7892-5973","affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045710726","display_name":"Bu Chen","orcid":"https://orcid.org/0009-0007-1332-6113"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bu Chen","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-1332-6113","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Min Li","orcid":"https://orcid.org/0009-0006-3517-4432"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Li","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-3517-4432","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035717003","display_name":"Wan Rui","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wan","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0002-8177-1677","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042052893","display_name":"Peiye Liu","orcid":"https://orcid.org/0000-0002-6568-5261"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peiye Liu","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6568-5261","affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100576340","display_name":"Yanheng Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanheng Lu","raw_affiliation_strings":["Alibaba Group, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-4024-6125","affiliations":[{"raw_affiliation_string":"Alibaba Group, Shanghai, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068606980","display_name":"Dimin Niu","orcid":"https://orcid.org/0000-0001-8440-3875"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimin Niu","raw_affiliation_strings":["Alibaba Group, Sunnyvale, USA"],"raw_orcid":"https://orcid.org/0000-0001-8440-3875","affiliations":[{"raw_affiliation_string":"Alibaba Group, Sunnyvale, USA","institution_ids":["https://openalex.org/I4210095624"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021863826","display_name":"Jinjia Zhou","orcid":"https://orcid.org/0000-0002-5078-0522"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jinjia Zhou","raw_affiliation_strings":["Hosei University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5078-0522","affiliations":[{"raw_affiliation_string":"Hosei University, Tokyo, Japan","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073266325","display_name":"Minge Jing","orcid":"https://orcid.org/0009-0005-0446-5600"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minge Jing","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-0446-5600","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085004179","display_name":"Yibo Fan","orcid":"https://orcid.org/0000-0003-2523-8261"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Fan","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2523-8261","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":14,"corresponding_author_ids":["https://openalex.org/A5089222298"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28820228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8626","last_page":"8635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9973000288009644,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9968000054359436,"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/unicorn","display_name":"Unicorn","score":0.7990999817848206},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.7035999894142151},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.6765000224113464},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4724999964237213},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4691999852657318},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4666999876499176},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4652999937534332},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.46050000190734863},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4058000147342682}],"concepts":[{"id":"https://openalex.org/C2780734062","wikidata":"https://www.wikidata.org/wiki/Q3549947","display_name":"Unicorn","level":2,"score":0.7990999817848206},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.7035999894142151},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.6765000224113464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6657000184059143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6657000184059143},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48170000314712524},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.46050000190734863},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.36959999799728394},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35740000009536743},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.3098999857902527},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C54243161","wikidata":"https://www.wikidata.org/wiki/Q39333","display_name":"Texture compression","level":5,"score":0.2992999851703644},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.2957000136375427},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.28859999775886536},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.2822999954223633},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2685999870300293},{"id":"https://openalex.org/C2778192920","wikidata":"https://www.wikidata.org/wiki/Q16874989","display_name":"Signal compression","level":4,"score":0.2667999863624573},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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":21,"referenced_works":["https://openalex.org/W1982471090","https://openalex.org/W2018140810","https://openalex.org/W2040903332","https://openalex.org/W2102166818","https://openalex.org/W2117539524","https://openalex.org/W2146395539","https://openalex.org/W2158395931","https://openalex.org/W2163714951","https://openalex.org/W2164931791","https://openalex.org/W2566079294","https://openalex.org/W2768814045","https://openalex.org/W2962785568","https://openalex.org/W2981613960","https://openalex.org/W3154567741","https://openalex.org/W3175457126","https://openalex.org/W3202918664","https://openalex.org/W4312806968","https://openalex.org/W4312933868","https://openalex.org/W4382462760","https://openalex.org/W4390872297","https://openalex.org/W4393185892"],"related_works":[],"abstract_inverted_index":{"Prevalent":[0],"lossy":[1],"image":[2,11,23,108,211],"compression":[3,12,24,188],"schemes":[4],"can":[5,103],"be":[6,216],"divided":[7],"into:":[8],"1)":[9],"explicit":[10,136],"(EIC),":[13],"including":[14],"traditional":[15],"standards":[16],"and":[17,89,132,147,162,177],"neural":[18,29,99,120],"end-to-end":[19],"algorithms;":[20],"2)":[21],"implicit":[22,28],"(IIC)":[25],"based":[26,152],"on":[27,153],"representations":[30],"(INR).":[31],"The":[32,119,213],"former":[33],"is":[34],"encountering":[35],"impasses":[36],"of":[37,45,94,127,141,150,194],"leveling":[38],"off":[39],"bitrate":[40],"reduction":[41,173],"at":[42],"a":[43,97,105,110,139],"cost":[44],"tremendous":[46],"complexity":[47],"while":[48,129],"the":[49,84,91,124,130,184,192],"latter":[50],"suffers":[51],"from":[52,109,183],"excessive":[53],"smoothing":[54],"quality":[55],"as":[56,58,86,123,191],"well":[57],"lengthy":[59],"decoder":[60,126],"models.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,71,143],"propose":[66,144],"an":[67,145],"innovative":[68],"paradigm,":[69],"which":[70],"dub":[72],"Unicorn":[73,102,151,206],"(Unified":[74],"Neural":[75],"Image":[76],"Compression":[77],"with":[78,114,157,175,207],"One":[79],"Nnumber":[80],"Reconstruction).":[81],"By":[82],"conceptualizing":[83],"images":[85,128,195],"index-image":[87],"pairs":[88,95],"learning":[90],"inherent":[92],"distribution":[93],"in":[96,210],"subtle":[98],"network":[100],"model,":[101],"reconstruct":[104],"visually":[106],"pleasing":[107],"randomly":[111],"generated":[112],"noise":[113],"only":[115],"one":[116],"index":[117],"number.":[118],"model":[121,159,202],"serves":[122],"unified":[125,185],"noises":[131],"indexes":[133],"corresponds":[134],"to":[135],"representations.":[137],"As":[138],"proof":[140],"concept,":[142],"effective":[146],"efficient":[148],"prototype":[149,169],"latent":[154],"diffusion":[155],"models":[156],"tailored":[158],"designs.":[160],"Quantitive":[161],"qualitative":[163],"experimental":[164],"results":[165],"demonstrate":[166],"that":[167,199],"our":[168,187],"achieves":[170],"significant":[171],"bitrates":[172],"compared":[174],"EIC":[176],"IIC":[178],"algorithms.":[179],"More":[180],"impressively,":[181],"benefitting":[182],"decoder,":[186],"ratio":[189],"escalates":[190],"quantity":[193],"increases.":[196],"We":[197],"envision":[198],"more":[200],"advanced":[201],"designs":[203],"will":[204,215],"endow":[205],"greater":[208],"potential":[209],"compression.":[212],"code":[214],"made":[217],"publicly":[218],"available":[219],"upon":[220],"publication.":[221]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-25T00:00:00"}
