{"id":"https://openalex.org/W3035205678","doi":"https://doi.org/10.1109/icme46284.2020.9102750","title":"Towards Coding For Human And Machine Vision: A Scalable Image Coding Approach","display_name":"Towards Coding For Human And Machine Vision: A Scalable Image Coding Approach","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3035205678","doi":"https://doi.org/10.1109/icme46284.2020.9102750","mag":"3035205678"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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/A5087570320","display_name":"Yueyu Hu","orcid":"https://orcid.org/0000-0003-4919-4515"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yueyu Hu","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736164","display_name":"Shuai Yang","orcid":"https://orcid.org/0000-0002-5576-8629"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Yang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070884682","display_name":"Wenhan Yang","orcid":"https://orcid.org/0000-0002-1692-0069"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhan Yang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024879728","display_name":"Ling\u2010Yu Duan","orcid":"https://orcid.org/0000-0002-4491-2023"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling-Yu Duan","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761525","display_name":"Jiaying Liu","orcid":"https://orcid.org/0000-0002-0468-9576"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaying Liu","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5087570320"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":3.7125,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.94478053,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.8126894235610962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7110699415206909},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6609261631965637},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5279908180236816},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5169681906700134},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.4928879737854004},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.4669910967350006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126894235610962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7110699415206909},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6609261631965637},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5279908180236816},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5169681906700134},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.4928879737854004},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4669910967350006},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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":29,"referenced_works":["https://openalex.org/W1977821862","https://openalex.org/W2099471712","https://openalex.org/W2129587342","https://openalex.org/W2133665775","https://openalex.org/W2140196014","https://openalex.org/W2151103935","https://openalex.org/W2161628678","https://openalex.org/W2161865688","https://openalex.org/W2170023599","https://openalex.org/W2186356322","https://openalex.org/W2249152912","https://openalex.org/W2331128040","https://openalex.org/W2343938449","https://openalex.org/W2556782416","https://openalex.org/W2593493485","https://openalex.org/W2749544970","https://openalex.org/W2786977213","https://openalex.org/W2798841107","https://openalex.org/W2949662773","https://openalex.org/W2950568498","https://openalex.org/W2963073614","https://openalex.org/W2963147844","https://openalex.org/W2963839617","https://openalex.org/W2971011627","https://openalex.org/W2982763192","https://openalex.org/W3104792420","https://openalex.org/W4320013936","https://openalex.org/W6704734575","https://openalex.org/W6748692466"],"related_works":["https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W3125091513","https://openalex.org/W4318832338","https://openalex.org/W4248383205","https://openalex.org/W4234745530","https://openalex.org/W3135697610","https://openalex.org/W2146383839","https://openalex.org/W2231829109","https://openalex.org/W2037153457"],"abstract_inverted_index":{"The":[0,123],"past":[1],"decades":[2],"have":[3],"witnessed":[4],"the":[5,15,21,28,31,38,61,64,80,88,129,137,172,178,197],"rapid":[6],"development":[7],"of":[8,17,30,40,117,144,180],"image":[9,55,95],"and":[10,43,63,71,86,99,136,171,188],"video":[11],"coding":[12,24,34,56],"techniques":[13],"in":[14,103,110,119,183],"era":[16],"big":[18],"data.":[19],"However,":[20],"signal":[22,149],"fidelity-driven":[23],"pipeline":[25],"design":[26],"limits":[27],"capability":[29],"existing":[32],"image/video":[33],"frameworks":[35],"to":[36,67,93,113,147,164],"fulfill":[37],"needs":[39],"both":[41,60,115,184],"machine":[42,69,133],"human":[44,72,152,185],"vision.":[45,153],"In":[46],"this":[47,111],"paper,":[48],"we":[49,159],"come":[50],"up":[51],"with":[52,97],"a":[53,120,142,161],"novel":[54],"framework":[57,182],"by":[58],"leveraging":[59],"compressive":[62],"generative":[65,89,157],"models,":[66,158],"support":[68],"vision":[70,118,134],"perception":[73],"tasks":[74],"jointly.":[75],"Given":[76],"an":[77],"input":[78],"image,":[79],"feature":[81,169],"analysis":[82],"is":[83,91,211],"first":[84],"applied,":[85],"then":[87],"model":[90],"employed":[92],"perform":[94],"reconstruction":[96],"features":[98],"additional":[100],"reference":[101,138,173],"pixels,":[102],"which":[104,192],"compact":[105,124,168],"edge":[106,125],"maps":[107],"are":[108],"extracted":[109],"work":[112],"connect":[114],"kinds":[116],"scalable":[121],"way.":[122],"map":[126],"serves":[127],"as":[128,141],"basic":[130],"layer":[131,146],"for":[132,151,206],"tasks,":[135],"pixels":[139],"act":[140],"sort":[143],"enhanced":[145],"guarantee":[148],"fidelity":[150],"By":[154],"introducing":[155],"advanced":[156],"train":[160],"flexible":[162],"network":[163],"reconstruct":[165],"images":[166],"from":[167],"representations":[170],"pixels.":[174],"Experimental":[175],"results":[176],"demonstrate":[177],"superiority":[179],"our":[181],"visual":[186],"quality":[187],"facial":[189],"landmark":[190],"detection,":[191],"provide":[193],"useful":[194],"evidence":[195],"on":[196,201],"emerging":[198],"standardization":[199],"efforts":[200],"MPEG":[202],"VCM":[203],"(Video":[204],"Coding":[205],"Machine).":[207],"Our":[208],"project":[209],"website":[210],"available":[212],"at":[213],"https://williamyang1991.github.io/projects/VCM-Face/.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":2}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}
