{"id":"https://openalex.org/W4386065752","doi":"https://doi.org/10.1109/cvpr52729.2023.01366","title":"GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis","display_name":"GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386065752","doi":"https://doi.org/10.1109/cvpr52729.2023.01366"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.01366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5102776884","display_name":"Ming Tao","orcid":"https://orcid.org/0000-0002-4662-7170"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Tao","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications","Peng Cheng Laboratory"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"Peng Cheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007962086","display_name":"Bing\u2010Kun Bao","orcid":"https://orcid.org/0000-0001-5956-831X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing-Kun Bao","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications","Peng Cheng Laboratory"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"Peng Cheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050748634","display_name":"Hao Tang","orcid":"https://orcid.org/0000-0002-2077-1246"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Tang","raw_affiliation_strings":["CVL, ETH Zürich"],"affiliations":[{"raw_affiliation_string":"CVL, ETH Zürich","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["Peng Cheng Laboratory","School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS)","MAIS, Institute of Automation, Chinese Academy of Sciences (CASIA)"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS)","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"MAIS, Institute of Automation, Chinese Academy of Sciences (CASIA)","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102776884"],"corresponding_institution_ids":["https://openalex.org/I41198531","https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":17.4903,"has_fulltext":false,"cited_by_count":144,"citation_normalized_percentile":{"value":0.9955181,"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":"14214","last_page":"14223"},"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":0.9991999864578247,"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":0.9991999864578247,"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":0.9915000200271606,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.988099992275238,"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/discriminator","display_name":"Discriminator","score":0.9120011925697327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8474818468093872},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.7814235091209412},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.665514349937439},{"id":"https://openalex.org/keywords/image-synthesis","display_name":"Image synthesis","score":0.5840789079666138},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5533063411712646},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5233756303787231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5231022834777832},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4531455636024475},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.4487244486808777},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.4259685277938843},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3358880281448364},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08202573657035828}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9120011925697327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8474818468093872},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7814235091209412},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.665514349937439},{"id":"https://openalex.org/C2989087649","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Image synthesis","level":3,"score":0.5840789079666138},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5533063411712646},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5233756303787231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5231022834777832},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4531455636024475},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.4487244486808777},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4259685277938843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3358880281448364},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08202573657035828},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.01366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":93,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1861492603","https://openalex.org/W2129069237","https://openalex.org/W2405756170","https://openalex.org/W2752796333","https://openalex.org/W2804078698","https://openalex.org/W2886641317","https://openalex.org/W2962845008","https://openalex.org/W2963163163","https://openalex.org/W2963612019","https://openalex.org/W2963799213","https://openalex.org/W2963966654","https://openalex.org/W2964024144","https://openalex.org/W2964216930","https://openalex.org/W2965289598","https://openalex.org/W2966792645","https://openalex.org/W2970562079","https://openalex.org/W2972328244","https://openalex.org/W3006538026","https://openalex.org/W3013529009","https://openalex.org/W3015093447","https://openalex.org/W3029699545","https://openalex.org/W3035500781","https://openalex.org/W3036167779","https://openalex.org/W3094502228","https://openalex.org/W3096601784","https://openalex.org/W3129576130","https://openalex.org/W3134582802","https://openalex.org/W3162926177","https://openalex.org/W3165647589","https://openalex.org/W3166396011","https://openalex.org/W3168053944","https://openalex.org/W3174525637","https://openalex.org/W3175528029","https://openalex.org/W3176641147","https://openalex.org/W3180355996","https://openalex.org/W3201409833","https://openalex.org/W4214485011","https://openalex.org/W4221143397","https://openalex.org/W4224035735","https://openalex.org/W4225307095","https://openalex.org/W4226125322","https://openalex.org/W4281485151","https://openalex.org/W4283388932","https://openalex.org/W4286869901","https://openalex.org/W4288089799","https://openalex.org/W4308163867","https://openalex.org/W4312388283","https://openalex.org/W4312438583","https://openalex.org/W4312805760","https://openalex.org/W4312911498","https://openalex.org/W4312933868","https://openalex.org/W4312977351","https://openalex.org/W4320526956","https://openalex.org/W4365421094","https://openalex.org/W4375928651","https://openalex.org/W4382317964","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6713645886","https://openalex.org/W6730746255","https://openalex.org/W6752378368","https://openalex.org/W6765779288","https://openalex.org/W6767137312","https://openalex.org/W6767384525","https://openalex.org/W6769627184","https://openalex.org/W6775704265","https://openalex.org/W6779823529","https://openalex.org/W6784333009","https://openalex.org/W6785719018","https://openalex.org/W6788990321","https://openalex.org/W6790978476","https://openalex.org/W6791276965","https://openalex.org/W6791353385","https://openalex.org/W6795288823","https://openalex.org/W6796242362","https://openalex.org/W6797359156","https://openalex.org/W6803132585","https://openalex.org/W6804432862","https://openalex.org/W6809396591","https://openalex.org/W6809885388","https://openalex.org/W6810125463","https://openalex.org/W6810471779","https://openalex.org/W6810595431","https://openalex.org/W6810601475","https://openalex.org/W6810792926","https://openalex.org/W6810940779","https://openalex.org/W6838515069","https://openalex.org/W6838639034","https://openalex.org/W6839643428","https://openalex.org/W6842255781","https://openalex.org/W6846655393","https://openalex.org/W6850085044"],"related_works":["https://openalex.org/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4293777179","https://openalex.org/W4385452045","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2332512904","https://openalex.org/W4224231624","https://openalex.org/W2319626700"],"abstract_inverted_index":{"Synthesizing":[0],"high-fidelity":[1],"complex":[2,107],"images":[3],"from":[4,133,187],"text":[5],"is":[6,201],"challenging.":[7],"Based":[8],"on":[9],"large":[10,23,168],"pretraining,":[11],"the":[12,52,89,96,114,119,130,183,194],"autoregressive":[13,170],"and":[14,40,66,76,98,138,143,148,160,171,181],"diffusion":[15,172],"models":[16,24,35],"can":[17],"synthesize":[18],"photo-realistic":[19],"images.":[20],"Although":[21],"these":[22],"have":[25],"shown":[26],"notable":[27],"progress,":[28],"there":[29],"remain":[30],"three":[31],"flaws.":[32],"1)":[33],"These":[34],"require":[36,67],"tremendous":[37],"training":[38,146,158],"data":[39,159],"parameters":[41],"to":[42,64,116,167],"achieve":[43],"good":[44],"performance.":[45],"2)":[46],"The":[47,58,106,140,189],"multi-step":[48],"generation":[49],"design":[50],"slows":[51],"image":[53,120],"synthesis":[54,179],"process":[55],"heavily.":[56],"3)":[57],"synthesized":[59],"visual":[60,131],"features":[61,137],"are":[62],"challenging":[63],"control":[65],"delicately":[68],"designed":[69],"prompts.":[70,139],"To":[71],"enable":[72],"high-quality,":[73],"efficient,":[74],"fast,":[75],"controllable":[77],"text-to-image":[78],"synthesis,":[79],"we":[80,101,123],"propose":[81,102,124],"Generative":[82],"Adversarial":[83],"CLIPs,":[84],"namely":[85],"GALIP.":[86,199],"GALIP":[87],"leverages":[88],"powerful":[90],"pretrained":[91,169],"CLIP":[92,112,134],"model":[93,153,176],"both":[94],"in":[95],"discriminator":[97,115,144],"generator.":[99],"Specifically,":[100],"a":[103,125,150],"CLIP-based":[104],"discriminator.":[105],"scene":[108],"understanding":[109],"ability":[110],"of":[111,197],"enables":[113],"accurately":[117],"assess":[118],"quality.":[121],"Furthermore,":[122],"CLIP-empowered":[126],"generator":[127,142],"that":[128],"induces":[129],"concepts":[132],"through":[135],"bridge":[136],"CLIP-integrated":[141],"boost":[145],"efficiency,":[147],"as":[149],"result,":[151],"our":[152,175,198],"only":[154],"requires":[155],"about":[156],"3%":[157],"6%":[161],"learnable":[162],"parameters,":[163],"achieving":[164],"comparable":[165],"results":[166,192],"models.":[173],"Moreover,":[174],"achieves":[177],"~120\u00d7faster":[178],"speed":[180],"inherits":[182],"smooth":[184],"latent":[185],"space":[186],"GAN.":[188],"extensive":[190],"experimental":[191],"demonstrate":[193],"excellent":[195],"performance":[196],"Code":[200],"available":[202],"at":[203],"https://github.com/tobran/GALIP.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":51},{"year":2024,"cited_by_count":74},{"year":2023,"cited_by_count":15}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}