{"id":"https://openalex.org/W2904759000","doi":"https://doi.org/10.1609/aaai.v33i01.33012564","title":"AI-Sketcher : A Deep Generative Model for Producing High-Quality Sketches","display_name":"AI-Sketcher : A Deep Generative Model for Producing High-Quality Sketches","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2904759000","doi":"https://doi.org/10.1609/aaai.v33i01.33012564","mag":"2904759000"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33012564","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33012564","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4103/3981","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4103/3981","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000474356","display_name":"Nan Cao","orcid":"https://orcid.org/0000-0003-1316-7515"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Cao","raw_affiliation_strings":["Tongji University"],"affiliations":[{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101539993","display_name":"Xin Yan","orcid":"https://orcid.org/0000-0002-5053-5447"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Yan","raw_affiliation_strings":["Tongji University"],"affiliations":[{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028730873","display_name":"Yang Shi","orcid":"https://orcid.org/0000-0003-1337-5322"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Shi","raw_affiliation_strings":["Tongji University"],"affiliations":[{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019987004","display_name":"Chaoran Chen","orcid":"https://orcid.org/0000-0002-6237-2999"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoran Chen","raw_affiliation_strings":["Tongji University"],"affiliations":[{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000474356"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":2.9524,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.9267951,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"2564","last_page":"2571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9970999956130981,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.8865046501159668},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8736146688461304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7981067299842834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6972519159317017},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6176925897598267},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5579570531845093},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5561769008636475},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5350839495658875},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5279991626739502},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5236168503761292},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5001423358917236},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3959771692752838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32965975999832153},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.24796339869499207},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10759210586547852}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.8865046501159668},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8736146688461304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7981067299842834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6972519159317017},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6176925897598267},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5579570531845093},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5561769008636475},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5350839495658875},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5279991626739502},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5236168503761292},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5001423358917236},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3959771692752838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32965975999832153},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.24796339869499207},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10759210586547852},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.33012564","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33012564","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4103/3981","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33012564","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33012564","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4103/3981","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904759000.pdf","grobid_xml":"https://content.openalex.org/works/W2904759000.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1503798456","https://openalex.org/W1522301498","https://openalex.org/W1810943226","https://openalex.org/W1881604308","https://openalex.org/W1959608418","https://openalex.org/W1965555277","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2131774270","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2185917628","https://openalex.org/W2187089797","https://openalex.org/W2467281799","https://openalex.org/W2493181180","https://openalex.org/W2603986758","https://openalex.org/W2606712314","https://openalex.org/W2703190149","https://openalex.org/W2754855391","https://openalex.org/W2762994800","https://openalex.org/W2776402438","https://openalex.org/W2799397159","https://openalex.org/W2962717182","https://openalex.org/W2962721615","https://openalex.org/W2962750131","https://openalex.org/W2963609389","https://openalex.org/W2963684088","https://openalex.org/W2963771763","https://openalex.org/W2963914894","https://openalex.org/W4243128585","https://openalex.org/W4293411878","https://openalex.org/W4298324432","https://openalex.org/W4299510085","https://openalex.org/W4320013936","https://openalex.org/W4394666973","https://openalex.org/W4394670483","https://openalex.org/W6640963894","https://openalex.org/W6641869264","https://openalex.org/W6666761814","https://openalex.org/W6679257740","https://openalex.org/W6719736630","https://openalex.org/W6723491766","https://openalex.org/W6745095357","https://openalex.org/W6751049920","https://openalex.org/W6751277268","https://openalex.org/W6753549681"],"related_works":["https://openalex.org/W3188573563","https://openalex.org/W4287064674","https://openalex.org/W3201246199","https://openalex.org/W4365211920","https://openalex.org/W3005996785","https://openalex.org/W3014948380","https://openalex.org/W4386984417","https://openalex.org/W2476099471","https://openalex.org/W2470043383","https://openalex.org/W4380551139"],"abstract_inverted_index":{"Sketch":[0],"drawings":[1],"play":[2],"an":[3,113],"important":[4],"role":[5],"in":[6,9,166],"assisting":[7],"humans":[8],"communication":[10],"and":[11,48,65,161],"creative":[12],"design":[13],"since":[14],"ancient":[15],"period.":[16],"This":[17],"situation":[18],"has":[19],"motivated":[20],"the":[21,60,100,107,120,129],"development":[22],"of":[23,62,103,122],"artificial":[24],"intelligence":[25],"(AI)":[26],"techniques":[27],"for":[28,45,83],"automatically":[29],"generating":[30,84,167],"sketches":[31,146],"based":[32,155],"on":[33,156],"user":[34],"input.":[35],"Sketch-RNN,":[36],"a":[37,51,79,95,139],"sequence-to-sequence":[38],"variational":[39],"autoencoder":[40,97],"(VAE)":[41],"model,":[42],"was":[43,153],"developed":[44],"this":[46],"purpose":[47],"known":[49],"as":[50],"state-of-the-art":[52],"technique.":[53],"However,":[54],"it":[55],"suffers":[56],"from":[57],"limitations,":[58],"including":[59],"generation":[61,121],"lowquality":[63],"results":[64,162],"its":[66,164],"incapability":[67],"to":[68,98,116,128],"support":[69,133],"multi-class":[70,134],"generations.":[71],"To":[72,132],"address":[73],"these":[74],"issues,":[75],"we":[76,137],"introduced":[77],"AI-Sketcher,":[78],"deep":[80],"generative":[81],"model":[82,89],"high-quality":[85,168],"multiclass":[86],"sketches.":[87,169],"Our":[88],"improves":[90],"drawing":[91],"quality":[92],"by":[93,125],"employing":[94],"CNN-based":[96],"capture":[99],"positional":[101],"information":[102],"each":[104,123],"stroke":[105,124],"at":[106],"pixel":[108],"level.":[109],"It":[110],"also":[111],"introduces":[112],"influence":[114],"layer":[115],"more":[117],"precisely":[118],"guide":[119],"directly":[126],"referring":[127],"training":[130],"data.":[131],"sketch":[135,159],"generation,":[136],"provided":[138],"conditional":[140],"vector":[141],"that":[142],"can":[143],"help":[144],"differentiate":[145],"under":[147],"various":[148],"classes.":[149],"The":[150],"proposed":[151],"technique":[152],"evaluated":[154],"two":[157],"large-scale":[158],"datasets,":[160],"demonstrated":[163],"power":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}