{"id":"https://openalex.org/W7154278448","doi":"https://doi.org/10.48550/arxiv.2604.11808","title":"Pair2Scene: Learning Local Object Relations for Procedural Scene Generation","display_name":"Pair2Scene: Learning Local Object Relations for Procedural Scene Generation","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7154278448","doi":"https://doi.org/10.48550/arxiv.2604.11808"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.11808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11808","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.2604.11808","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114126985","display_name":"Xingjian Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ran, Xingjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133612873","display_name":"Shujie Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shujie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005246543","display_name":"Weipeng Zhong","orcid":"https://orcid.org/0000-0001-7279-1575"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Weipeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108057378","display_name":"Li Luo","orcid":"https://orcid.org/0000-0002-2413-2257"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133608484","display_name":"Bo Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Bo","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":0.3312999904155731,"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":0.3312999904155731,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.22930000722408295,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.11420000344514847,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6862000226974487},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.5963000059127808},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5056999921798706},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45840001106262207},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.424699991941452},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.36959999799728394},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.35499998927116394},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.3521000146865845},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.3395000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758400022983551},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6862000226974487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6219000220298767},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.5963000059127808},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45840001106262207},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.424699991941452},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3675000071525574},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3521000146865845},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3212999999523163},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3003000020980835},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.11808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11808","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.2604.11808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11808","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generating":[0],"high-fidelity":[1],"3D":[2],"indoor":[3],"scenes":[4,32,153],"remains":[5],"a":[6,70,114,136,160],"significant":[7],"challenge":[8],"due":[9],"to":[10,25,30,143,167],"data":[11,142,192],"scarcity":[12],"and":[13,83,102,127,196],"the":[14,39,49,130,145],"complexity":[15],"of":[16,48,60,92,121,129],"modeling":[17],"intricate":[18],"spatial":[19,43,118],"relations.":[20],"Current":[21],"methods":[22,183],"often":[23],"struggle":[24],"scale":[26],"beyond":[27,190],"training":[28,191],"distribution":[29],"dense":[31],"or":[33],"rely":[34],"on":[35,46,56,125],"LLMs/VLMs":[36],"that":[37,51,75,98,105,178,188],"lack":[38],"ability":[40],"for":[41],"precise":[42],"reasoning.":[44],"Building":[45],"top":[47],"observation":[50],"object":[52],"placement":[53],"relies":[54],"mainly":[55,88],"local":[57,78,169],"dependencies":[58],"instead":[59],"information-redundant":[61],"global":[62,173],"distributions,":[63],"in":[64,184],"this":[65],"paper,":[66],"we":[67,134],"propose":[68],"Pair2Scene,":[69],"novel":[71],"procedural":[72],"generation":[73],"framework":[74,150,180],"integrates":[76],"learned":[77],"rules":[79,87,112,170],"with":[80],"scene":[81,141],"hierarchies":[82],"physics-based":[84],"algorithms.":[85],"These":[86],"capture":[89],"two":[90],"types":[91],"inter-object":[93],"relations,":[94],"namely":[95],"support":[96],"relations":[97,104],"follow":[99],"physical":[100,195],"hierarchies,":[101],"functional":[103],"reflect":[106],"semantic":[107,197],"links.":[108],"We":[109],"model":[110,158],"these":[111],"through":[113],"network,":[115],"which":[116],"estimates":[117],"position":[119,126],"distributions":[120],"dependent":[122],"objects":[123],"conditioned":[124],"geometry":[128],"anchor":[131],"ones.":[132],"Accordingly,":[133],"curate":[135],"dataset":[137],"3D-Pairs":[138],"from":[139],"existing":[140,182],"train":[144],"model.":[146],"During":[147],"inference,":[148],"our":[149,157,179],"can":[151],"generate":[152],"by":[154],"recursively":[155],"applying":[156],"within":[159],"hierarchical":[161],"structure,":[162],"leveraging":[163],"collision-aware":[164],"rejection":[165],"sampling":[166],"align":[168],"into":[171],"coherent":[172],"layouts.":[174],"Extensive":[175],"experiments":[176],"demonstrate":[177],"outperforms":[181],"generating":[185],"complex":[186],"environments":[187],"go":[189],"while":[193],"maintaining":[194],"plausibility.":[198]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}