{"id":"https://openalex.org/W3199888436","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533925","title":"Text to Image Synthesis based on Multi - Perspective Fusion","display_name":"Text to Image Synthesis based on Multi - Perspective Fusion","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199888436","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533925","mag":"3199888436"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5019348755","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0002-2408-366X"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Zhiqiang Zhang","raw_affiliation_strings":["Graduate School of Science and Engineering Hosei University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering Hosei University, Tokyo, Japan","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039118363","display_name":"Chen Fu","orcid":"https://orcid.org/0000-0001-6554-1770"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chen Fu","raw_affiliation_strings":["Graduate School of Science and Engineering Hosei University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering Hosei University, Tokyo, Japan","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021863826","display_name":"Jinjia Zhou","orcid":"https://orcid.org/0000-0002-5078-0522"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jinjia Zhou","raw_affiliation_strings":["Graduate School of Science and Engineering Hosei University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering Hosei University, Tokyo, Japan","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049814360","display_name":"Wenxin Yu","orcid":"https://orcid.org/0000-0002-6093-5516"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Yu","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101759345","display_name":"Ning Jiang","orcid":"https://orcid.org/0000-0003-0794-7996"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5019348755"],"corresponding_institution_ids":["https://openalex.org/I204291657"],"apc_list":null,"apc_paid":null,"fwci":0.2882,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55882353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9986000061035156,"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":0.9986000061035156,"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":0.998199999332428,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9966999888420105,"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":0.7719838619232178},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7297799587249756},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6850631237030029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.626701295375824},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6078459620475769},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5904976725578308},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5471526384353638},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5366204977035522},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5091986060142517},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5009560585021973},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4763634204864502},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4631596803665161},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45424824953079224},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3644777536392212},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.0629352331161499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7719838619232178},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7297799587249756},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6850631237030029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.626701295375824},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6078459620475769},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5904976725578308},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5471526384353638},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5366204977035522},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5091986060142517},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5009560585021973},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4763634204864502},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4631596803665161},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45424824953079224},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3644777536392212},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0629352331161499},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W648143168","https://openalex.org/W1522301498","https://openalex.org/W1797268635","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1861492603","https://openalex.org/W1893585201","https://openalex.org/W1909320841","https://openalex.org/W1921523184","https://openalex.org/W1959608418","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2183341477","https://openalex.org/W2184218725","https://openalex.org/W2194775991","https://openalex.org/W2267126114","https://openalex.org/W2405756170","https://openalex.org/W2423557781","https://openalex.org/W2530372461","https://openalex.org/W2557449848","https://openalex.org/W2785678896","https://openalex.org/W2890923031","https://openalex.org/W2951523806","https://openalex.org/W2953318193","https://openalex.org/W2962741254","https://openalex.org/W2962845008","https://openalex.org/W2962897886","https://openalex.org/W2963150697","https://openalex.org/W2963163163","https://openalex.org/W2963184176","https://openalex.org/W2963373786","https://openalex.org/W2963413689","https://openalex.org/W2963448850","https://openalex.org/W2963636093","https://openalex.org/W2963684088","https://openalex.org/W2963836885","https://openalex.org/W2963966654","https://openalex.org/W2963981733","https://openalex.org/W2964024144","https://openalex.org/W2964121744","https://openalex.org/W2964216930","https://openalex.org/W2965289598","https://openalex.org/W2966792645","https://openalex.org/W2970562079","https://openalex.org/W2972328244","https://openalex.org/W4300838842","https://openalex.org/W4301206121","https://openalex.org/W4320013936","https://openalex.org/W6621378261","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6639118987","https://openalex.org/W6639204139","https://openalex.org/W6639732818","https://openalex.org/W6640185926","https://openalex.org/W6640963894","https://openalex.org/W6678815747","https://openalex.org/W6685352114","https://openalex.org/W6686131816","https://openalex.org/W6713645886","https://openalex.org/W6718379498","https://openalex.org/W6728889164","https://openalex.org/W6748582592","https://openalex.org/W6765779288","https://openalex.org/W6767137312","https://openalex.org/W6767384525","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W4293320219","https://openalex.org/W2953246223","https://openalex.org/W4283584549","https://openalex.org/W2554314924","https://openalex.org/W4288256692","https://openalex.org/W2998859928","https://openalex.org/W4381885966","https://openalex.org/W2969399009","https://openalex.org/W4398186750","https://openalex.org/W3151498616"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,22],"propose":[4],"a":[5,24],"multi-perspective":[6],"fusion":[7],"method":[8,27,43,80,113],"to":[9,28,60,116],"improve":[10,61],"the":[11,17,20,30,34,40,49,55,58,66,85,117],"performance":[12],"of":[13,19,57,69,73],"text-to-image":[14],"synthesis.":[15],"From":[16],"perspective":[18,56],"generator,":[21],"introduce":[23],"dynamic":[25],"selection":[26],"make":[29],"text":[31],"feature":[32,37],"match":[33],"corresponding":[35],"image":[36,47],"better,":[38],"while":[39],"multi-class":[41],"discriminant":[42],"with":[44],"mask":[45],"segmentation":[46],"as":[48],"extra":[50],"type":[51],"is":[52,114],"introduced":[53],"from":[54],"discriminator":[59],"its":[62],"discrimination":[63],"ability.":[64],"Through":[65],"effective":[67],"integration":[68],"these":[70],"two":[71],"aspects":[72],"improvement,":[74],"more":[75],"excellent":[76],"results":[77],"by":[78],"our":[79,100,112],"are":[81],"obtained.":[82],"Experiments":[83],"on":[84],"Caltech-UCSD":[86],"Birds":[87],"200":[88],"(CUB)":[89],"and":[90,103,107],"Microsoft":[91],"Common":[92],"Objects":[93],"in":[94],"Context":[95],"(MS":[96],"COCO)":[97],"datasets":[98],"demonstrate":[99],"method's":[101],"effectiveness":[102],"superiority.":[104],"The":[105],"qualitative":[106],"quantitative":[108],"experiments":[109],"validate":[110],"that":[111],"superior":[115],"existing":[118],"state-of-the-art":[119],"methods.":[120]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}