{"id":"https://openalex.org/W3159310825","doi":"https://doi.org/10.1145/3444685.3446275","title":"Hungry networks","display_name":"Hungry networks","publication_year":2021,"publication_date":"2021-03-07","ids":{"openalex":"https://openalex.org/W3159310825","doi":"https://doi.org/10.1145/3444685.3446275","mag":"3159310825"},"language":"en","primary_location":{"id":"doi:10.1145/3444685.3446275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3444685.3446275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","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/A5053879697","display_name":"Shu Naritomi","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shu Naritomi","raw_affiliation_strings":["The University of Electro-Communications, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054600485","display_name":"\u202aKeiji Yanai\u202c","orcid":"https://orcid.org/0000-0002-0431-183X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keiji Yanai","raw_affiliation_strings":[""],"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053879697"],"corresponding_institution_ids":["https://openalex.org/I20529979"],"apc_list":null,"apc_paid":null,"fwci":0.5254,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.5893135,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.97079998254776,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7774159908294678},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6173612475395203},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5943518877029419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5603461265563965},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5134502649307251},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48976898193359375}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7774159908294678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6173612475395203},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5943518877029419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5603461265563965},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5134502649307251},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48976898193359375},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3444685.3446275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3444685.3446275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1987648924","https://openalex.org/W1992642990","https://openalex.org/W2008073424","https://openalex.org/W2053825465","https://openalex.org/W2057352599","https://openalex.org/W2105997696","https://openalex.org/W2206370378","https://openalex.org/W2229412420","https://openalex.org/W2527142681","https://openalex.org/W2560722161","https://openalex.org/W2765652171","https://openalex.org/W2810185362","https://openalex.org/W2824941129","https://openalex.org/W2902811116","https://openalex.org/W2980340092","https://openalex.org/W4231051073","https://openalex.org/W4233857083","https://openalex.org/W4247102052"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2058170566","https://openalex.org/W2036807459","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2079911747"],"abstract_inverted_index":{"Dietary":[0],"calorie":[1,19,36],"management":[2],"has":[3],"been":[4,22],"an":[5,101,106,180],"important":[6],"topic":[7],"in":[8,24,46,84,118],"recent":[9],"years,":[10],"and":[11,14,71,73,105,175],"various":[12],"methods":[13,32],"applications":[15],"on":[16,56],"image-based":[17],"food":[18,35,166,189],"estimation":[20],"have":[21],"published":[23],"the":[25,30,43,86,94,113,148,151,155,184,188,192,195,206,214,218,225,244],"multimedia":[26],"community.":[27],"Most":[28],"of":[29,33,67,100,123,133,142,150,154,164,172,186,194,217,240],"existing":[31,234],"estimating":[34],"amounts":[37],"use":[38],"2D-based":[39],"image":[40],"recognition.":[41],"On":[42],"other":[44],"hand,":[45],"this":[47,119,242],"paper,":[48],"we":[49],"would":[50],"like":[51],"to":[52,182,223,247],"make":[53],"inferences":[54],"based":[55],"3D":[57,65,87,103,108,134,165,170,215,238,250],"volume":[58,185,226,252],"for":[59],"more":[60],"accurate":[61],"estimation.":[62],"We":[63,82,177],"performed":[64],"reconstruction":[66],"a":[68,74,79,97,126,137,161,200,249,254],"dish":[69,104,256],"(food":[70],"plate)":[72],"plate":[75,98,143,152],"(without":[76],"foods),":[77],"from":[78,136,191,253],"single":[80,138,255],"image.":[81,139,257],"succeeded":[83],"restoring":[85],"shape":[88,216],"with":[89,227],"high":[90],"accuracy":[91],"while":[92],"maintaining":[93],"consistency":[95,144],"between":[96],"part":[99],"estimated":[102,107],"plate.":[109],"To":[110],"achieve":[111],"this,":[112],"following":[114],"contributions":[115],"were":[116],"made":[117],"paper.":[120],"(1)":[121],"Proposal":[122],"\"Hungry":[124],"Networks,\"":[125],"new":[127,162,208],"network":[128],"that":[129,146,168,205,236],"generates":[130],"two":[131,156,196],"kinds":[132],"volumes":[135],"(2)":[140],"Introduction":[141],"loss":[145,209],"matches":[147,213],"shapes":[149,239],"parts":[153],"reconstructed":[157,197],"models.":[158],"(3)":[159],"Creating":[160],"dataset":[163],"models":[167],"are":[169,232],"scanned":[171],"actual":[173],"foods":[174],"plates.":[176],"also":[178,221],"conducted":[179],"experiment":[181],"infer":[183],"only":[187,212],"region":[190],"difference":[193],"volumes.":[198],"As":[199],"result,":[201],"it":[202],"was":[203],"shown":[204],"introduced":[207],"function":[210],"not":[211],"plate,":[219],"but":[220],"contributes":[222],"obtaining":[224],"higher":[228],"accuracy.":[229],"Although":[230],"there":[231],"some":[233],"studies":[235],"consider":[237],"foods,":[241],"is":[243],"first":[245],"study":[246],"generate":[248],"mesh":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-05-10T00:00:00"}