{"id":"https://openalex.org/W2977272401","doi":"https://doi.org/10.1109/ijcnn.2019.8852389","title":"Fashion Outfit Composition Combining Sequential Learning and Deep Aesthetic Network","display_name":"Fashion Outfit Composition Combining Sequential Learning and Deep Aesthetic Network","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977272401","doi":"https://doi.org/10.1109/ijcnn.2019.8852389","mag":"2977272401"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852389","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5003378750","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0002-5765-0827"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Computer Science and Software Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046411806","display_name":"Hongyan Quan","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Quan","raw_affiliation_strings":["School of Computer Science and Software Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003378750"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1256393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9975000023841858,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9922999739646912,"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":0.7680097818374634},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7053366899490356},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.49979591369628906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46017634868621826},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.45980018377304077},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.39041274785995483},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34948787093162537},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07850560545921326}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7680097818374634},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7053366899490356},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.49979591369628906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46017634868621826},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.45980018377304077},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.39041274785995483},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34948787093162537},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07850560545921326},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852389","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1001964002","https://openalex.org/W1511924373","https://openalex.org/W2009678853","https://openalex.org/W2027731328","https://openalex.org/W2038147967","https://openalex.org/W2048835603","https://openalex.org/W2073751126","https://openalex.org/W2091473544","https://openalex.org/W2115091888","https://openalex.org/W2135367695","https://openalex.org/W2144499799","https://openalex.org/W2146851707","https://openalex.org/W2151103935","https://openalex.org/W2157732827","https://openalex.org/W2183341477","https://openalex.org/W2200092826","https://openalex.org/W2221507685","https://openalex.org/W2294624972","https://openalex.org/W2409850953","https://openalex.org/W2471768434","https://openalex.org/W2471933213","https://openalex.org/W2483053118","https://openalex.org/W2523978282","https://openalex.org/W2593649459","https://openalex.org/W2593887162","https://openalex.org/W2604528050","https://openalex.org/W2609373935","https://openalex.org/W2737102415","https://openalex.org/W2741249238","https://openalex.org/W2747102465","https://openalex.org/W2764273117","https://openalex.org/W2772328249","https://openalex.org/W2788663865","https://openalex.org/W2795117763","https://openalex.org/W2887712318","https://openalex.org/W2890502958","https://openalex.org/W2963290108","https://openalex.org/W3098379913","https://openalex.org/W3099462466","https://openalex.org/W3100153382","https://openalex.org/W3101830194","https://openalex.org/W4294238563","https://openalex.org/W6689235694","https://openalex.org/W6697253549","https://openalex.org/W6734429903","https://openalex.org/W6734531890","https://openalex.org/W6743006830","https://openalex.org/W6747590370"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353752728"],"abstract_inverted_index":{"A":[0],"proper":[1,189],"outfit":[2,45],"should":[3],"consist":[4],"of":[5,8,85,126,140,156],"different":[6],"categories":[7],"items":[9,89],"that":[10,106,172,185,199,206],"are":[11],"visually":[12],"compatible":[13],"and":[14,55,138,210],"share":[15],"a":[16,74],"similar":[17],"style.":[18],"Besides,":[19],"personal":[20,178,193,208],"aesthetic":[21,39,57,66,113,154,163,173,194,204],"preference":[22],"is":[23,97,151,161,174],"also":[24,145],"an":[25,30,61,91,94,131],"important":[26],"criterion":[27],"when":[28],"creating":[29],"overall":[31],"outfit.":[32,92,132],"Nevertheless,":[33],"only":[34],"few":[35],"studies":[36],"deal":[37],"with":[38,177],"information":[40],"in":[41,90,130],"previous":[42],"work":[43],"on":[44,166],"composition.":[46],"In":[47,69],"this":[48],"paper,":[49],"we":[50,71,118,144,180,186],"exploit":[51],"both":[52],"sequential":[53],"learning":[54],"deep":[56],"network":[58],"to":[59,81,99,122,134,192],"train":[60],"end-to-end":[62],"model":[63,80,96,104,109],"for":[64],"composing":[65,162],"outfits":[67,164,190,205],"automatically.":[68],"detail,":[70],"firstly":[72],"introduce":[73],"bidirectional":[75],"long":[76],"short-term":[77],"memory":[78],"(Bi-LSTM)":[79],"discover":[82],"the":[83,102,107,112,124,136,141,153,167,183,212],"concept":[84],"compatibility":[86],"among":[87],"fashion":[88,128,169],"Then,":[93],"aesthetic-based":[95],"proposed":[98,142],"parallel":[100],"supervise":[101],"Bi-LSTM":[103],"so":[105],"trained":[108],"can":[110,187,202],"capture":[111],"features":[114],"from":[115],"outfits.":[116,158],"Meanwhile,":[117],"leverage":[119],"visual-semantic":[120],"descriptions":[121],"guarantee":[123],"uniqueness":[125],"each":[127],"item":[129],"Moreover,":[133],"evaluate":[135],"effectiveness":[137],"practicability":[139],"model,":[143],"design":[146],"two":[147],"representative":[148],"tasks.":[149],"One":[150],"evaluating":[152],"scores":[155],"existing":[157],"The":[159],"other":[160],"conditioned":[165],"given":[168],"item.":[170],"Considering":[171],"highly":[175],"correlated":[176],"preference,":[179],"additionally":[181],"conduct":[182],"experiment":[184],"create":[188],"according":[191],"preferences.":[195],"Extensive":[196],"experiments":[197],"indicate":[198],"our":[200],"method":[201],"generate":[203],"meet":[207],"preferences":[209],"outperform":[211],"state-of-the-art.":[213]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
