{"id":"https://openalex.org/W4413145559","doi":"https://doi.org/10.1109/cvpr52734.2025.00743","title":"Generative Photomontage","display_name":"Generative Photomontage","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4413145559","doi":"https://doi.org/10.1109/cvpr52734.2025.00743"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52734.2025.00743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.00743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5112932187","display_name":"Sean J. Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sean J. Liu","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000827309","display_name":"Nupur Kumari","orcid":"https://orcid.org/0000-0003-1799-1069"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nupur Kumari","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022467818","display_name":"Ariel Shamir","orcid":"https://orcid.org/0000-0001-7082-7845"},"institutions":[{"id":"https://openalex.org/I2801151526","display_name":"Brandman University","ror":"https://ror.org/013922990","country_code":"US","type":"education","lineage":["https://openalex.org/I2801151526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ariel Shamir","raw_affiliation_strings":["Reichman University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reichman University","institution_ids":["https://openalex.org/I2801151526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102883508","display_name":"Jun-Yan Zhu","orcid":"https://orcid.org/0000-0001-8504-3410"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun-Yan Zhu","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2554088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7931","last_page":"7941"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.6395000219345093,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.6395000219345093,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6189972758293152},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5584582090377808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3979560136795044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6189972758293152},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5584582090377808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3979560136795044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52734.2025.00743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.00743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2380075625","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Text-to-image":[0],"models":[1],"are":[2],"powerful":[3],"tools":[4],"for":[5,40,147,168],"image":[6,26,44,178],"creation.":[7],"However,":[8],"the":[9,42,69,83,99,104,118,131],"generation":[10],"process":[11],"is":[12],"akin":[13],"to":[14,22],"a":[15,24,30,38,57,61,87,93,108,122],"dice":[16],"roll":[17],"and":[18,73,115,158,160,171,181],"makes":[19],"it":[20,47],"difficult":[21],"achieve":[23],"single":[25],"that":[27,96,140,173],"captures":[28],"everything":[29],"user":[31],"wants.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36,76],"propose":[37],"framework":[39,143],"creating":[41],"desired":[43,80],"by":[45,66],"compositing":[46,135],"from":[48,82],"various":[49,182],"parts":[50,81],"of":[51,63],"generated":[52,65,84,105],"images,":[53],"in":[54,98,111],"essence":[55],"forming":[56],"Generative":[58],"Photomontage.":[59],"Given":[60],"stack":[62],"images":[64,106],"ControlNet":[67],"using":[68,86,107],"same":[70],"input":[71],"condition":[72],"different":[74],"seeds,":[75],"let":[77],"users":[78],"select":[79],"results":[85,167],"brush":[88,101],"stroke":[89],"interface.":[90],"We":[91,138,164],"introduce":[92],"novel":[94],"technique":[95],"takes":[97],"user\u2019s":[100],"strokes,":[102],"segments":[103],"graph-based":[109],"optimization":[110],"diffusion":[112],"feature":[113],"space,":[114],"then":[116],"composites":[117],"segmented":[119],"regions":[120,133],"via":[121],"new":[123,152],"feature-space":[124],"blending":[125,179],"method.":[126],"Our":[127],"method":[128,175],"faithfully":[129],"preserves":[130],"user-selected":[132],"while":[134],"them":[136],"harmoniously.":[137],"demonstrate":[139,172],"our":[141,174],"flexible":[142],"can":[144],"be":[145],"used":[146],"many":[148],"applications,":[149],"including":[150],"generating":[151],"appearance":[153],"combinations,":[154],"fixing":[155],"incorrect":[156],"shapes":[157],"artifacts,":[159],"improving":[161],"prompt":[162],"alignment.":[163],"show":[165],"compelling":[166],"each":[169],"application":[170],"outperforms":[176],"existing":[177],"methods":[180],"baselines.":[183]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
