{"id":"https://openalex.org/W4389217314","doi":"https://doi.org/10.48550/arxiv.2311.17261","title":"SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors","display_name":"SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors","publication_year":2023,"publication_date":"2023-11-28","ids":{"openalex":"https://openalex.org/W4389217314","doi":"https://doi.org/10.48550/arxiv.2311.17261"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.17261","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.17261","pdf_url":"https://arxiv.org/pdf/2311.17261","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.17261","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026731366","display_name":"Dave Zhenyu Chen","orcid":"https://orcid.org/0000-0002-3883-1905"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Dave Zhenyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100629469","display_name":"Haoxuan Li","orcid":"https://orcid.org/0000-0002-3483-4914"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoxuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114488729","display_name":"Hsin-Ying Lee","orcid":"https://orcid.org/0009-0001-5252-1137"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Hsin-Ying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058028206","display_name":"Sergey Tulyakov","orcid":"https://orcid.org/0000-0003-3465-1592"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tulyakov, Sergey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088583491","display_name":"Matthias Nie\u00dfner","orcid":"https://orcid.org/0000-0001-6093-5199"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie\u00dfner, Matthias","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5026731366"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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":0.9868999719619751,"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":0.9868999719619751,"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":0.9807999730110168,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9781000018119812,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7172821164131165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673867106437683},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.657747745513916},{"id":"https://openalex.org/keywords/texture-synthesis","display_name":"Texture synthesis","score":0.6551104187965393},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6327646970748901},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5992293357849121},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5214987397193909},{"id":"https://openalex.org/keywords/bidirectional-texture-function","display_name":"Bidirectional texture function","score":0.4620811939239502},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.43750476837158203},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4253879487514496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.385726660490036},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.37929239869117737},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29584959149360657},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25443750619888306},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.12256431579589844}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7172821164131165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673867106437683},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.657747745513916},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.6551104187965393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6327646970748901},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5992293357849121},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5214987397193909},{"id":"https://openalex.org/C165164221","wikidata":"https://www.wikidata.org/wiki/Q261078","display_name":"Bidirectional texture function","level":5,"score":0.4620811939239502},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.43750476837158203},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4253879487514496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.385726660490036},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.37929239869117737},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29584959149360657},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25443750619888306},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.12256431579589844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2311.17261","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.17261","pdf_url":"https://arxiv.org/pdf/2311.17261","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.17261","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.17261","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":"pmh:oai:arXiv.org:2311.17261","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.17261","pdf_url":"https://arxiv.org/pdf/2311.17261","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G6052429835","display_name":null,"funder_award_id":"(DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389217314.pdf","grobid_xml":"https://content.openalex.org/works/W4389217314.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2036879703","https://openalex.org/W2003873690","https://openalex.org/W2626505278","https://openalex.org/W2359713774","https://openalex.org/W2743128629","https://openalex.org/W4200432310","https://openalex.org/W1983661653","https://openalex.org/W2183887509","https://openalex.org/W2355987747","https://openalex.org/W1649930874"],"abstract_inverted_index":{"We":[0,81],"propose":[1],"SceneTex,":[2],"a":[3,30,71,87,105],"novel":[4],"method":[5],"for":[6,13,130],"effectively":[7],"generating":[8],"high-quality":[9],"and":[10,41,60,126,139],"style-consistent":[11],"textures":[12],"indoor":[14],"scenes":[15],"using":[16],"depth-to-image":[17],"diffusion":[18,35],"priors.":[19],"Unlike":[20],"previous":[21],"methods":[22],"that":[23],"either":[24],"iteratively":[25],"warp":[26],"2D":[27],"views":[28],"onto":[29],"mesh":[31,79],"surface":[32],"or":[33],"distillate":[34],"latent":[36],"features":[37],"without":[38],"accurate":[39,127],"geometric":[40],"style":[42,59,99],"cues,":[43],"SceneTex":[44,69,123],"formulates":[45],"the":[46,55,78,83,98,110,116,143],"texture":[47,73,85,128,145],"synthesis":[48,129],"task":[49],"as":[50],"an":[51],"optimization":[52],"problem":[53],"in":[54,91,120,136],"RGB":[56,93,111],"space":[57],"where":[58],"geometry":[61],"consistency":[62,100],"are":[63],"properly":[64],"reflected.":[65],"At":[66],"its":[67],"core,":[68],"proposes":[70],"multiresolution":[72],"field":[74],"to":[75,108,115],"implicitly":[76],"encode":[77],"appearance.":[80],"optimize":[82],"target":[84],"via":[86],"score-distillation-based":[88],"objective":[89],"function":[90],"respective":[92],"renderings.":[94],"To":[95],"further":[96],"secure":[97],"across":[101],"views,":[102],"we":[103],"introduce":[104],"cross-attention":[106],"decoder":[107],"predict":[109],"values":[112],"by":[113],"cross-attending":[114],"pre-sampled":[117],"reference":[118],"locations":[119],"each":[121],"instance.":[122],"enables":[124],"various":[125],"3D-FRONT":[131],"scenes,":[132],"demonstrating":[133],"significant":[134],"improvements":[135],"visual":[137],"quality":[138],"prompt":[140],"fidelity":[141],"over":[142],"prior":[144],"generation":[146],"methods.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2023-12-01T00:00:00"}