{"id":"https://openalex.org/W4399318010","doi":"https://doi.org/10.1109/wacv61042.2026.00129","title":"Mixed Diffusion for 3D Indoor Scene Synthesis","display_name":"Mixed Diffusion for 3D Indoor Scene Synthesis","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W4399318010","doi":"https://doi.org/10.1109/wacv61042.2026.00129"},"language":"en","primary_location":{"id":"doi:10.1109/wacv61042.2026.00129","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.21066","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072422674","display_name":"Siyi Hu","orcid":"https://orcid.org/0000-0002-0686-5182"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyi Hu","raw_affiliation_strings":["Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079863730","display_name":"Diego Mart\u00ecn Arroyo","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Martin Arroyo","raw_affiliation_strings":["Google, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Inc","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002339863","display_name":"Stephanie Debats","orcid":"https://orcid.org/0000-0002-9514-5442"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephanie Debats","raw_affiliation_strings":["Google, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Inc","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006401089","display_name":"Fabian Manhardt","orcid":"https://orcid.org/0000-0002-4577-4590"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fabian Manhardt","raw_affiliation_strings":["Google, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Inc","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042157108","display_name":"Luca Carlone","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luca Carlone","raw_affiliation_strings":["Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041092666","display_name":"Federico Tombari","orcid":"https://orcid.org/0000-0001-5598-5212"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Federico Tombari","raw_affiliation_strings":["Google, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Inc","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00088475,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1262","last_page":"1272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9921000003814697,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9921000003814697,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9842000007629395,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9717000126838684,"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/diffusion","display_name":"Diffusion","score":0.5845470428466797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4340527057647705},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.39861127734184265},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3442907929420471},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.34104177355766296},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.32187390327453613},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12400606274604797}],"concepts":[{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5845470428466797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4340527057647705},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.39861127734184265},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3442907929420471},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.34104177355766296},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.32187390327453613},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12400606274604797},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wacv61042.2026.00129","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2405.21066","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.21066","pdf_url":"https://arxiv.org/pdf/2405.21066","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2405.21066","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2405.21066","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2405.21066","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.21066","pdf_url":"https://arxiv.org/pdf/2405.21066","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399318010.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2386796262","https://openalex.org/W372519479","https://openalex.org/W3177740930","https://openalex.org/W2356683864","https://openalex.org/W1484549928","https://openalex.org/W1974805659","https://openalex.org/W2811388477","https://openalex.org/W2418025259"],"abstract_inverted_index":{"Generating":[0],"realistic":[1],"3D":[2,20,106,174],"scenes":[3,108],"is":[4,65],"an":[5],"area":[6],"of":[7,129],"growing":[8],"interest":[9],"in":[10,47,73,154,172,193],"computer":[11],"vision":[12],"and":[13,29,113,126,137,149,169,196],"robotics.":[14],"However,":[15,52],"creating":[16],"high-quality,":[17],"diverse":[18],"synthetic":[19],"content":[21],"often":[22],"requires":[23,70],"expert":[24],"intervention,":[25],"making":[26],"it":[27,69,178],"costly":[28],"complex.":[30],"Recently,":[31],"efforts":[32],"to":[33,56,103],"automate":[34],"this":[35,91],"process":[36],"with":[37],"learning":[38],"techniques,":[39],"particularly":[40],"diffusion":[41,54,87,100,170],"models,":[42],"have":[43],"shown":[44],"significant":[45],"improvements":[46],"tasks":[48],"like":[49],"furniture":[50,197],"rearrangement.":[51],"applying":[53],"models":[55,171],"floor-conditioned":[57,173],"indoor":[58,107],"scene":[59,119,175,194],"synthesis":[60],"remains":[61],"under-explored.":[62],"This":[63],"task":[64],"especially":[66],"challenging":[67],"as":[68],"arranging":[71],"objects":[72],"continuous":[74,150],"space":[75],"while":[76],"selecting":[77],"from":[78],"discrete":[79,147],"object":[80,182],"categories,":[81],"posing":[82],"unique":[83],"difficulties":[84],"for":[85,158],"conventional":[86],"methods.":[88],"To":[89],"bridge":[90],"gap,":[92],"we":[93],"present":[94],"MiDiffusion,":[95],"a":[96,110,118,122,127,155,185],"novel":[97],"mixed":[98,146],"discrete-continuous":[99],"model":[101],"designed":[102],"synthesize":[104],"plausible":[105],"given":[109],"floor":[111,124],"plan":[112,125],"pre-arranged":[114],"objects.":[115],"We":[116],"represent":[117],"layout":[120],"by":[121,133],"2D":[123],"set":[128],"objects,":[130],"each":[131],"defined":[132],"category,":[134],"location,":[135],"size,":[136],"orientation.":[138],"Our":[139],"approach":[140],"uniquely":[141],"applies":[142],"structured":[143],"corruption":[144],"across":[145],"semantic":[148],"geometric":[151],"domains,":[152],"resulting":[153],"better-conditioned":[156],"problem":[157],"denoising.":[159],"Evaluated":[160],"on":[161],"the":[162],"3D-FRONT":[163],"dataset,":[164],"MiDiffusion":[165],"outperforms":[166],"state-of-the-art":[167],"autoregressive":[168],"synthesis.":[176],"Additionally,":[177],"effectively":[179],"handles":[180],"partial":[181],"constraints":[183],"via":[184],"corruption-and-masking":[186],"strategy":[187],"without":[188],"task-specific":[189],"training,":[190],"demonstrating":[191],"advantages":[192],"completion":[195],"arrangement":[198],"tasks.":[199]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}