{"id":"https://openalex.org/W7154205523","doi":"https://doi.org/10.48550/arxiv.2604.10268","title":"EditCrafter: Tuning-free High-Resolution Image Editing via Pretrained Diffusion Model","display_name":"EditCrafter: Tuning-free High-Resolution Image Editing via Pretrained Diffusion Model","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154205523","doi":"https://doi.org/10.48550/arxiv.2604.10268"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10268","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":null,"license_id":null,"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.2604.10268","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104127572","display_name":"Kunho Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Kunho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133609652","display_name":"Sumin Seo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seo, Sumin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133552502","display_name":"Yongjun Cho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Yongjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006604581","display_name":"Hyungjin Chung","orcid":"https://orcid.org/0000-0003-3202-0893"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chung, Hyungjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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":0.5630999803543091,"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":0.5630999803543091,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.08529999852180481,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.014700000174343586,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image-editing","display_name":"Image editing","score":0.9535999894142151},{"id":"https://openalex.org/keywords/video-editing","display_name":"Video editing","score":0.5995000004768372},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.576200008392334},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49459999799728394},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.41940000653266907},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.38769999146461487}],"concepts":[{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.9535999894142151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8342999815940857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6220999956130981},{"id":"https://openalex.org/C2780310081","wikidata":"https://www.wikidata.org/wiki/Q1154312","display_name":"Video editing","level":2,"score":0.5995000004768372},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.576200008392334},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5569999814033508},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.41940000653266907},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.38769999146461487},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3695000112056732},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C87829876","wikidata":"https://www.wikidata.org/wiki/Q648877","display_name":"Post-production","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10268","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10268","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,134],"propose":[1,136],"EditCrafter,":[2,110],"a":[3,42,111,137],"high-resolution":[4,132],"image":[5,53,149],"editing":[6,49,54,66,96,115,150,165],"method":[7],"that":[8,143,158],"operates":[9,118],"without":[10,170],"tuning,":[11],"leveraging":[12],"pretrained":[13],"text-to-image":[14],"(T2I)":[15],"diffusion":[16,36,61],"models":[17,37,62],"to":[18,71,73],"process":[19],"images":[20,74],"at":[21,86],"resolutions":[22,81,89,169],"significantly":[23],"exceeding":[24],"those":[25],"used":[26],"during":[27],"training.":[28],"Leveraging":[29],"the":[30,39,87,126,130,152,159],"generative":[31],"priors":[32],"of":[33,41,45,129],"large-scale":[34],"T2I":[35],"enables":[38],"development":[40],"wide":[43],"array":[44],"novel":[46],"generation":[47],"and":[48,63,102,172],"applications.":[50],"Although":[51],"numerous":[52],"methods":[55],"have":[56],"been":[57],"proposed":[58],"based":[59],"on":[60],"exhibit":[64],"high-quality":[65],"results,":[67],"they":[68,83],"are":[69],"difficult":[70],"apply":[72],"with":[75,98],"arbitrary":[76],"aspect":[77],"ratios":[78],"or":[79,91],"higher":[80],"since":[82],"only":[84],"work":[85],"training":[88],"(512x512":[90],"1024x1024).":[92],"Naively":[93],"applying":[94],"patch-wise":[95],"fails":[97],"unrealistic":[99],"object":[100],"structures":[101],"repetition.":[103],"To":[104],"address":[105],"these":[106],"challenges,":[107],"we":[108],"introduce":[109],"simple":[112],"yet":[113],"effective":[114],"pipeline.":[116],"EditCrafter":[117,161],"by":[119],"first":[120],"performing":[121],"tiled":[122],"inversion,":[123],"which":[124],"preserves":[125],"original":[127],"identity":[128],"input":[131],"image.":[133],"further":[135],"noise-damped":[138],"manifold-constrained":[139],"classifier-free":[140],"guidance":[141],"(NDCFG++)":[142],"is":[144],"tailored":[145],"for":[146],"high":[147],"resolution":[148],"from":[151],"inverted":[153],"latent.":[154],"Our":[155],"experiments":[156],"show":[157],"our":[160],"can":[162],"achieve":[163],"impressive":[164],"results":[166],"across":[167],"various":[168],"fine-tuning":[171],"optimization.":[173]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-15T00:00:00"}
