{"id":"https://openalex.org/W7155538952","doi":"https://doi.org/10.48550/arxiv.2604.21052","title":"StyleVAR: Controllable Image Style Transfer via Visual Autoregressive Modeling","display_name":"StyleVAR: Controllable Image Style Transfer via Visual Autoregressive Modeling","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155538952","doi":"https://doi.org/10.48550/arxiv.2604.21052"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.21052","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21052","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.21052","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134510771","display_name":"Liqi Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing, Liqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022388376","display_name":"Dingming Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Dingming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038896379","display_name":"\u674e\u6c9b\u5e74","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Peinian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132777973","display_name":"Lichen Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Lichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xu, Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Xing, Hanyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Hanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.9635000228881836,"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":0.9635000228881836,"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/T11448","display_name":"Face recognition and analysis","score":0.005100000184029341,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/autoregressive-model","display_name":"Autoregressive model","score":0.7092000246047974},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5928999781608582},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5023999810218811},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.453900009393692},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.44699999690055847},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4097999930381775},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4000000059604645}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7092000246047974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6319000124931335},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5928999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167999863624573},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5023999810218811},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.453900009393692},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4000000059604645},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.36340001225471497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34200000762939453},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33230000734329224},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.31060001254081726},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.28189998865127563},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.21052","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21052","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.21052","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21052","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5017222166061401}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,130],"build":[1],"on":[2,48,143,192,216,240],"the":[3,42,67,98,109,116,120,125,204,211,217,222,249],"Visual":[4],"Autoregressive":[5],"Modeling":[6],"(VAR)":[7],"framework":[8],"and":[9,29,50,56,78,103,119,183,200,203,233,243,255],"formulate":[10],"style":[11,49,55,77,102,121],"transfer":[12],"as":[13,82],"conditional":[14],"discrete":[15,32],"sequence":[16],"modeling":[17],"in":[18,65,133],"a":[19,35,37,61,137,144,162,237],"learned":[20],"latent":[21],"space.":[22],"Images":[23],"are":[24],"decomposed":[25],"into":[26,31],"multi-scale":[27,175],"representations":[28],"tokenized":[30],"codes":[33],"by":[34,152],"VQ-VAE;":[36],"transformer":[38],"then":[39],"autoregressively":[40],"models":[41],"distribution":[43],"of":[44,88,101,128,148],"target":[45,69],"tokens":[46],"conditioned":[47],"content":[51,57,79,104,117,253],"tokens.":[52],"To":[53],"inject":[54],"information,":[58],"we":[59],"introduce":[60],"blended":[62],"cross-attention":[63],"mechanism":[64],"which":[66,86],"evolving":[68],"representation":[70,111],"attends":[71],"to":[72,91,112,170],"its":[73],"own":[74],"history,":[75],"while":[76,226,236],"features":[80],"act":[81],"queries":[83],"that":[84],"decide":[85],"aspects":[87],"this":[89],"history":[90],"emphasize.":[92],"A":[93],"scale-dependent":[94],"blending":[95],"coefficient":[96],"controls":[97],"relative":[99],"influence":[100],"at":[105],"each":[106],"stage,":[107],"encouraging":[108],"synthesized":[110],"align":[113],"with":[114,155,166,245],"both":[115],"structure":[118],"texture":[122,225],"without":[123],"breaking":[124],"autoregressive":[126],"continuity":[127],"VAR.":[129],"train":[131],"StyleVAR":[132,186],"two":[134],"stages":[135],"from":[136],"pretrained":[138],"VAR":[139],"checkpoint:":[140],"supervised":[141],"fine-tuning":[142,154],"large":[145],"triplet":[146],"dataset":[147],"content--style--target":[149],"images,":[150],"followed":[151],"reinforcement":[153],"Group":[156],"Relative":[157],"Policy":[158],"Optimization":[159],"(GRPO)":[160],"against":[161],"DreamSim-based":[163],"perceptual":[164,219],"reward,":[165],"per-action":[167],"normalization":[168],"weighting":[169],"rebalance":[171],"credit":[172],"across":[173],"VAR's":[174],"hierarchy.":[176],"Across":[177],"three":[178],"benchmarks":[179],"spanning":[180],"in-,":[181],"near-,":[182],"out-of-distribution":[184],"regimes,":[185],"consistently":[187],"outperforms":[188],"an":[189],"AdaIN":[190],"baseline":[191],"Style":[193],"Loss,":[194,196],"Content":[195],"LPIPS,":[197],"SSIM,":[198],"DreamSim,":[199],"CLIP":[201],"similarity,":[202],"GRPO":[205],"stage":[206],"yields":[207],"further":[208],"gains":[209],"over":[210],"SFT":[212],"checkpoint,":[213],"most":[214],"notably":[215],"reward-aligned":[218],"metrics.":[220],"Qualitatively,":[221],"method":[223],"transfers":[224],"maintaining":[227],"semantic":[228],"structure,":[229],"especially":[230],"for":[231,251],"landscapes":[232],"architectural":[234],"scenes,":[235],"generalization":[238],"gap":[239],"internet":[241],"images":[242],"difficulty":[244],"human":[246],"faces":[247],"highlight":[248],"need":[250],"better":[252],"diversity":[254],"stronger":[256],"structural":[257],"priors.":[258]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-25T00:00:00"}
