{"id":"https://openalex.org/W4285981784","doi":"https://doi.org/10.1145/3528233.3530738","title":"StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets","display_name":"StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets","publication_year":2022,"publication_date":"2022-07-20","ids":{"openalex":"https://openalex.org/W4285981784","doi":"https://doi.org/10.1145/3528233.3530738"},"language":"en","primary_location":{"id":"doi:10.1145/3528233.3530738","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3528233.3530738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings","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/A5028042143","display_name":"Axel Sauer","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]},{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Axel Sauer","raw_affiliation_strings":["University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany","institution_ids":["https://openalex.org/I4210135521","https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110696266","display_name":"Katja Schwarz","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]},{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katja Schwarz","raw_affiliation_strings":["University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany","institution_ids":["https://openalex.org/I4210135521","https://openalex.org/I8087733"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016606943","display_name":"Andreas Geiger","orcid":"https://orcid.org/0000-0002-8151-3726"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]},{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Geiger","raw_affiliation_strings":["University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen, Germany and Max Planck Institute for Intelligent Systems, Germany","institution_ids":["https://openalex.org/I4210135521","https://openalex.org/I8087733"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028042143"],"corresponding_institution_ids":["https://openalex.org/I4210135521","https://openalex.org/I8087733"],"apc_list":null,"apc_paid":null,"fwci":28.541,"has_fulltext":false,"cited_by_count":286,"citation_normalized_percentile":{"value":0.99822185,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9968000054359436,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9968000054359436,"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":0.9911999702453613,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.98089998960495,"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":0.6281710863113403},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5961399674415588},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14192107319831848},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.04556483030319214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6281710863113403},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5961399674415588},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14192107319831848},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.04556483030319214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3528233.3530738","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3528233.3530738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2560674852","https://openalex.org/W2890748873","https://openalex.org/W2962770929","https://openalex.org/W2963105487","https://openalex.org/W2985068832","https://openalex.org/W3003162010","https://openalex.org/W3026885507","https://openalex.org/W3035574324","https://openalex.org/W3035653890","https://openalex.org/W3094954720","https://openalex.org/W3096147990","https://openalex.org/W3102061158","https://openalex.org/W3159647175","https://openalex.org/W3175528029","https://openalex.org/W3178406257","https://openalex.org/W3207918547","https://openalex.org/W4287332295","https://openalex.org/W6748655329"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Computer":[0],"graphics":[1],"has":[2],"experienced":[3],"a":[4,88,106,121,127],"recent":[5],"surge":[6],"of":[7,123,144],"data-centric":[8],"approaches":[9],"for":[10,22,45,57],"photorealistic":[11],"and":[12,28,87,113,137,152],"controllable":[13],"content":[14],"creation.":[15],"StyleGAN":[16,42],"in":[17],"particular":[18],"sets":[19,105],"new":[20,107],"standards":[21],"generative":[23],"modeling":[24],"regarding":[25],"image":[26,111],"quality":[27],"controllability.":[29],"However,":[30],"StyleGAN\u2019s":[31],"performance":[32],"severely":[33],"degrades":[34],"on":[35,99,109],"large":[36],"unstructured":[37],"datasets":[38],"such":[39,126],"as":[40],"ImageNet.":[41,100],"was":[43],"designed":[44],"controllability;":[46],"hence,":[47],"prior":[48],"works":[49],"suspect":[50],"its":[51],"restrictive":[52],"design":[53],"to":[54,68,92,117],"be":[55,69,156],"unsuitable":[56],"diverse":[58],"datasets.":[59],"In":[60],"contrast,":[61],"we":[62,81],"find":[63],"the":[64,70,75,95,115,141],"main":[65],"limiting":[66],"factor":[67],"current":[71],"training":[72],"strategy.":[73],"Following":[74],"recently":[76],"introduced":[77],"Projected":[78],"GAN":[79],"paradigm,":[80],"leverage":[82],"powerful":[83],"neural":[84],"network":[85],"priors":[86],"progressive":[89],"growing":[90],"strategy":[91],"successfully":[93],"train":[94],"latest":[96],"StyleGAN3":[97],"generator":[98],"Our":[101],"final":[102],"model,":[103],"StyleGAN-XL,":[104],"state-of-the-art":[108],"large-scale":[110],"synthesis":[112],"is":[114],"first":[116],"generate":[118],"images":[119,139],"at":[120,125,158],"resolution":[122],"10242":[124],"dataset":[128],"scale.":[129],"We":[130],"demonstrate":[131],"that":[132],"this":[133],"model":[134],"can":[135,155],"invert":[136],"edit":[138],"beyond":[140],"narrow":[142],"domain":[143],"portraits":[145],"or":[146],"specific":[147],"object":[148],"classes.":[149],"Code,":[150],"models,":[151],"supplementary":[153],"videos":[154],"found":[157],"https://sites.google.com/view/stylegan-xl/":[159],".":[160]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":74},{"year":2024,"cited_by_count":118},{"year":2023,"cited_by_count":75},{"year":2022,"cited_by_count":13}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
