{"id":"https://openalex.org/W7161708789","doi":"https://doi.org/10.48550/arxiv.2605.16990","title":"DreamEdit3D: Personalization of Multi-View Diffusion Models for 3D Editing","display_name":"DreamEdit3D: Personalization of Multi-View Diffusion Models for 3D Editing","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161708789","doi":"https://doi.org/10.48550/arxiv.2605.16990"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16990","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16990","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.16990","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136479339","display_name":"Jinxin Ai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ai, Jinxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136495483","display_name":"Matthias Nie\u00dfner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie\u00dfner, Matthias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5042694681","display_name":"Ziya Erko\u00e7","orcid":"https://orcid.org/0000-0003-2656-3680"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erko\u00e7, Ziya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.741599977016449,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.741599977016449,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.1023000031709671,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10789","display_name":"Interactive and Immersive Displays","score":0.03739999979734421,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/personalization","display_name":"Personalization","score":0.730400025844574},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6204000115394592},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46149998903274536},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.435699999332428},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4115000069141388},{"id":"https://openalex.org/keywords/image-editing","display_name":"Image editing","score":0.34049999713897705},{"id":"https://openalex.org/keywords/video-editing","display_name":"Video editing","score":0.3237000107765198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7979000210762024},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.730400025844574},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46149998903274536},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.41780000925064087},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.366100013256073},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.34049999713897705},{"id":"https://openalex.org/C2780310081","wikidata":"https://www.wikidata.org/wiki/Q1154312","display_name":"Video editing","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30160000920295715},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.2985000014305115},{"id":"https://openalex.org/C72414096","wikidata":"https://www.wikidata.org/wiki/Q1367461","display_name":"Mass customization","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16990","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16990","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.16990","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16990","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"2D":[1,34,139],"diffusion":[2,98],"models":[3],"have":[4],"achieved":[5],"remarkable":[6],"success":[7],"in":[8],"identity-preserving":[9],"personalization,":[10],"extending":[11],"this":[12],"capability":[13],"to":[14,22,67,110,141,151],"3D":[15,44,56,122],"assets":[16],"remains":[17],"a":[18,38,55,81],"significant":[19],"challenge":[20],"due":[21],"the":[23,136],"complexities":[24],"of":[25,96,138],"multi-view":[26,86,97,112],"consistency":[27],"and":[28,62,147],"spatial":[29],"control.":[30],"Inspired":[31],"by":[32,93],"these":[33,102],"advancements,":[35],"we":[36,58],"present":[37],"novel":[39],"personalization":[40,140],"method":[41,133],"for":[42,77],"text-guided":[43],"editing":[45,108,128],"that":[46,131],"enables":[47],"compositional,":[48],"object-level":[49,64],"control":[50],"through":[51,80],"natural":[52],"language.":[53],"Given":[54],"input,":[57],"render":[59],"orthogonal":[60],"views":[61],"extract":[63],"segmentation":[65],"masks":[66],"isolate":[68],"semantic":[69],"components.":[70],"We":[71],"then":[72],"learn":[73],"distinct":[74],"token":[75],"embeddings":[76],"each":[78],"component":[79],"tailored":[82],"two-phase":[83],"optimization":[84],"strategy:":[85],"textual":[87],"inversion":[88],"with":[89,107],"attention":[90],"alignment,":[91],"followed":[92],"full":[94],"fine-tuning":[95],"model.":[99],"During":[100],"inference,":[101],"disentangled":[103],"tokens":[104],"seamlessly":[105],"compose":[106],"prompts":[109],"generate":[111],"consistent":[113],"images,":[114],"which":[115],"are":[116],"subsequently":[117],"lifted":[118],"into":[119],"high-fidelity":[120],"textured":[121],"meshes.":[123],"Extensive":[124],"evaluations":[125],"across":[126],"diverse":[127],"scenarios":[129],"demonstrate":[130],"our":[132],"successfully":[134],"transfers":[135],"flexibility":[137],"3D,":[142],"achieving":[143],"state-of-the-art":[144],"edit":[145],"faithfulness":[146],"identity":[148],"preservation":[149],"compared":[150],"existing":[152],"baselines.":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}
