{"id":"https://openalex.org/W4385484694","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191980","title":"Anime Character Identification and Tag Prediction by Multimodality Modeling: Dataset and Model","display_name":"Anime Character Identification and Tag Prediction by Multimodality Modeling: Dataset and Model","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385484694","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191980"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/A5100430783","display_name":"Yi Fan","orcid":"https://orcid.org/0000-0002-1494-434X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fan Yi","raw_affiliation_strings":["School of Computer Science, Fudan University,Shanghai,China","School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011348984","display_name":"Jiaxiang Wu","orcid":"https://orcid.org/0000-0001-9132-5625"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxiang Wu","raw_affiliation_strings":["Youtu Lab Tencent,Shanghai,China","Youtu Lab Tencent, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Youtu Lab Tencent,Shanghai,China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Youtu Lab Tencent, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045420812","display_name":"Minyi Zhao","orcid":"https://orcid.org/0000-0001-7720-806X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minyi Zhao","raw_affiliation_strings":["School of Computer Science, Fudan University,Shanghai,China","School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017862559","display_name":"Shuigeng Zhou","orcid":"https://orcid.org/0000-0002-1949-2768"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuigeng Zhou","raw_affiliation_strings":["School of Computer Science, Fudan University,Shanghai,China","School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100430783"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.2456,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51449362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9957000017166138,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9957000017166138,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9937000274658203,"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":0.9747999906539917,"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/anime","display_name":"Anime","score":0.9270706176757812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8059755563735962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6466761827468872},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6116585731506348},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5743753910064697},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5308564305305481},{"id":"https://openalex.org/keywords/animation","display_name":"Animation","score":0.5028881430625916},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.4937988221645355},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4751424789428711},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.47205549478530884},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.41946378350257874},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.4119224548339844},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3981618881225586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35314059257507324},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15490520000457764},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1488504409790039},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.09960409998893738}],"concepts":[{"id":"https://openalex.org/C118130439","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Anime","level":2,"score":0.9270706176757812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8059755563735962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6466761827468872},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6116585731506348},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5743753910064697},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5308564305305481},{"id":"https://openalex.org/C502989409","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Animation","level":2,"score":0.5028881430625916},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.4937988221645355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4751424789428711},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.47205549478530884},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.41946378350257874},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.4119224548339844},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3981618881225586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35314059257507324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15490520000457764},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1488504409790039},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.09960409998893738},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2018561248","https://openalex.org/W2021003221","https://openalex.org/W2109586012","https://openalex.org/W2112912048","https://openalex.org/W2130371234","https://openalex.org/W2192954843","https://openalex.org/W2251394420","https://openalex.org/W2270470215","https://openalex.org/W2277195237","https://openalex.org/W2295038166","https://openalex.org/W2296073425","https://openalex.org/W2471768434","https://openalex.org/W2574577332","https://openalex.org/W2595360966","https://openalex.org/W2786335506","https://openalex.org/W2787433253","https://openalex.org/W2798951647","https://openalex.org/W2886641317","https://openalex.org/W2896457183","https://openalex.org/W2951183276","https://openalex.org/W2963457656","https://openalex.org/W2966715458","https://openalex.org/W3093203468","https://openalex.org/W3101659800","https://openalex.org/W3123911204","https://openalex.org/W3126792443","https://openalex.org/W3142849873","https://openalex.org/W3166396011","https://openalex.org/W3176641147","https://openalex.org/W3177224328","https://openalex.org/W3184735396","https://openalex.org/W3197298035","https://openalex.org/W3208314443","https://openalex.org/W3209532394","https://openalex.org/W4226182655","https://openalex.org/W4312412113","https://openalex.org/W4312680644","https://openalex.org/W4385245566","https://openalex.org/W6639102338","https://openalex.org/W6676497082","https://openalex.org/W6676647902","https://openalex.org/W6739901393","https://openalex.org/W6766904570","https://openalex.org/W6789753369","https://openalex.org/W6791353385","https://openalex.org/W6798805250","https://openalex.org/W6811013733"],"related_works":["https://openalex.org/W2075421999","https://openalex.org/W4241725891","https://openalex.org/W4400692277","https://openalex.org/W4247978692","https://openalex.org/W592941694","https://openalex.org/W4200085573","https://openalex.org/W2378422373","https://openalex.org/W3091774296","https://openalex.org/W4289597193","https://openalex.org/W2500902696"],"abstract_inverted_index":{"In":[0,55],"recent":[1],"years,":[2],"some":[3],"advances":[4],"have":[5],"been":[6],"achieved":[7],"in":[8,79,97,109,184,202],"classification":[9],"and":[10,27,46,70,186],"object":[11],"detection":[12],"related":[13,44,189],"to":[14,32,48,52,99],"animation.":[15],"However,":[16],"these":[17],"works":[18],"do":[19],"not":[20,115],"take":[21],"full":[22],"advantage":[23],"of":[24,94,151,159],"the":[25,33,43,92,111,126,157,164,175,181,188],"tags":[26,153],"text":[28,83],"description":[29],"content":[30],"attached":[31],"anime":[34,86,133,171,182],"data":[35,47],"when":[36],"they":[37],"are":[38],"created,":[39],"which":[40],"restricts":[41],"both":[42],"methods":[45],"unimodality,":[49],"consequently":[50],"leading":[51],"unsatisfactory":[53],"performance.":[54],"this":[56,162],"paper,":[57],"we":[58,90,129,178],"propose":[59],"a":[60,131],"novel":[61],"multimodal":[62,75,121,170],"deep":[63,122],"learning":[64,96],"network":[65],"for":[66,119,169],"Anime":[67],"character":[68,172],"identification":[69],"tag":[71],"prediction":[72],"by":[73],"exploiting":[74],"data.":[76],"Considering":[77],"that":[78,110,137,193],"many":[80],"realistic":[81],"scenarios,":[82],"annotations":[84],"accompanying":[85],"may":[87],"be":[88],"missing,":[89],"introduce":[91],"concept":[93],"curriculum":[95],"transformers":[98],"enable":[100],"inference":[101],"with":[102,148],"only":[103],"one":[104],"modality.":[105],"Another":[106],"challenge":[107],"lies":[108],"existing":[112],"dataset":[113,134,166],"does":[114],"meet":[116],"our":[117,160,194],"demand":[118],"large-scale":[120],"learning.":[123],"To":[124,156],"train":[125],"proposed":[127],"network,":[128,177],"construct":[130],"new":[132],"Dan:":[135,200],"mul":[136,201],"contains":[138],"over":[139],"1.6M":[140],"images":[141,185],"spread":[142],"across":[143],"more":[144],"than":[145],"14K":[146],"categories,":[147],"an":[149],"average":[150],"24":[152],"per":[154],"image.":[155],"best":[158],"knowledge,":[161],"is":[163],"first":[165],"specifically":[167],"designed":[168],"identification.":[173,204],"With":[174],"trained":[176],"can":[179],"identify":[180],"characters":[183],"generate":[187],"tags.":[190],"Experiments":[191],"show":[192],"method":[195],"achieves":[196],"state-of-the-art":[197],"performance":[198],"on":[199],"animation":[203]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}