乐胖代购免代理版

{"id":"https://openalex.org/W2902889463","doi":"https://doi.org/10.1109/icpr.2018.8545633","title":"Facial Attribute Editing by Latent Space Adversarial Variational Autoencoders","display_name":"Facial Attribute Editing by Latent Space Adversarial Variational Autoencoders","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902889463","doi":"https://doi.org/10.1109/icpr.2018.8545633","mag":"2902889463"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545633","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5101999863","display_name":"Defang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defang Li","raw_affiliation_strings":["Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403020","display_name":"Min Zhang","orcid":"https://orcid.org/0009-0002-1427-6721"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021656787","display_name":"Weifu Chen","orcid":"https://orcid.org/0000-0002-9375-2214"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifu Chen","raw_affiliation_strings":["Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090531329","display_name":"Guocan Feng","orcid":"https://orcid.org/0000-0002-0097-5591"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guocan Feng","raw_affiliation_strings":["Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Province Key Laboratory, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.071,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":4,"citation_normalized_percentile":{"value":0.376192,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":77,"max":79},"biblio":{"volume":null,"issue":null,"first_page":"1337","last_page":"1342"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9995,"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":0.9995,"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/T11448","display_name":"Face recognition and analysis","score":0.9969,"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":0.9889,"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/discriminative-model","display_name":"Discriminative model","score":0.57397014},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.52140045},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4404354},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.4353292}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70700896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.67213774},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.57397014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5384917},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.52140045},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.50499254},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.50223255},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4569732},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.44058797},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4404354},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.4353292},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.38149095},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.21924493},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545633","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.65}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":46,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1691728462","https://openalex.org/W1834627138","https://openalex.org/W1850742715","https://openalex.org/W1909320841","https://openalex.org/W1924619199","https://openalex.org/W1959608418","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2126398289","https://openalex.org/W2135354436","https://openalex.org/W2139427956","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2269752429","https://openalex.org/W2411541852","https://openalex.org/W2412320034","https://openalex.org/W2524985544","https://openalex.org/W2528578439","https://openalex.org/W2536132686","https://openalex.org/W2552611751","https://openalex.org/W2553897675","https://openalex.org/W2579578355","https://openalex.org/W2585630030","https://openalex.org/W2594537814","https://openalex.org/W2606418751","https://openalex.org/W2621350877","https://openalex.org/W2770587987","https://openalex.org/W2962741254","https://openalex.org/W2962793481","https://openalex.org/W2962808998","https://openalex.org/W2962897886","https://openalex.org/W2963073614","https://openalex.org/W2963567641","https://openalex.org/W2963767194","https://openalex.org/W2963865839","https://openalex.org/W2963920537","https://openalex.org/W2964121744","https://openalex.org/W2964144352","https://openalex.org/W2964167449","https://openalex.org/W2964193438","https://openalex.org/W4293398859","https://openalex.org/W4293568373","https://openalex.org/W4294568686","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W4386184937","https://openalex.org/W4384918963","https://openalex.org/W2995777218","https://openalex.org/W2937349443","https://openalex.org/W2153939756","https://openalex.org/W2128027845","https://openalex.org/W2105231718","https://openalex.org/W2093104230","https://openalex.org/W2019680624","https://openalex.org/W1493875009"],"abstract_inverted_index":{"This":[0],"work":[1],"focuses":[2],"on":[3,123,227],"the":[4,45,61,64,72,100,124,127,132,168,184,190,193,196,203,214,219,223,228],"problem":[5],"of":[6,14,66,112,126],"editing":[7],"facial":[8],"images":[9,208],"by":[10,34,71],"manipulating":[11],"specified":[12,24,169],"attributes":[13,170,240],"interest.":[15],"To":[16],"learn":[17],"latent":[18,197,220],"representations":[19],"disentangled":[20],"with":[21,107],"respect":[22],"to":[23,144,206,213],"face":[25,239,244],"attribute,":[26],"a":[27,57,139,146,149,152,165],"novel":[28],"attribute-disentangled":[29],"generative":[30,40],"model":[31,205,224],"is":[32,74,142,148,199],"proposed":[33,46,204],"combining":[35],"variational":[36],"autoencoders":[37],"(VAEs)":[38],"and":[39,56,81,94,175,192,231,241],"adversarial":[41,185],"networks":[42],"(GANs).":[43],"In":[44],"model,":[47],"only":[48,137],"two":[49,77],"deep":[50],"mappings":[51],"are":[52,211],"included:":[53],"an":[54,158],"encoder":[55,73,128,133],"decoder,":[58],"similarly":[59],"as":[60,90,103,129,138,157],"counterparts":[62],"in":[63,182,195,218,237],"context":[65],"VAEs.":[67],"Latent":[68],"space":[69,80,198],"mapped":[70],"split":[75],"into":[76],"parts:":[78],"style":[79,191],"attribute":[82,159,194],"space.":[83,221],"The":[84,97],"former":[85],"represents":[86,99,116],"attribute-irrelevant":[87],"factors,":[88],"such":[89,102],"identity,":[91],"position,":[92],"illumination":[93],"background,":[95],"etc.":[96],"latter":[98],"attributes,":[101],"hair":[104],"color,":[105],"gender,":[106],"or":[108,151,171],"without":[109],"glasses,":[110],"etc,":[111],"which":[113,201],"each":[114],"dimension":[115],"one":[117],"single":[118],"attribute.":[119],"By":[120],"regarding":[121],"constraints":[122],"output":[125],"discriminative":[130],"objectives,":[131],"can":[134,162],"act":[135],"not":[136],"discriminator":[140],"that":[141,161],"expected":[143],"discriminate":[145,163],"sample":[147,166],"real":[150,215],"generated":[153],"one,":[154],"but":[155],"also":[156],"classifier":[160],"whether":[164],"has":[167],"not.":[172],"Combining":[173],"reconstruction":[174],"Kullback-Leibler":[176],"(KL)":[177],"divergence":[178],"regularization":[179],"losses":[180],"like":[181],"VAEs,":[183],"training":[186],"loss":[187],"defined":[188],"for":[189],"introduced,":[200],"drives":[202],"generate":[207],"whose":[209],"distribution":[210,217],"close":[212],"data":[216],"Finally,":[222],"was":[225],"evaluated":[226],"CelebA":[229],"dataset":[230],"experimental":[232],"results":[233],"showed":[234],"its":[235],"effectiveness":[236],"disentangling":[238],"generating":[242],"high-quality":[243],"images.":[245]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2902889463","counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-01-08T06:02:21.694854","created_date":"2018-12-11"}