{"id":"https://openalex.org/W7162308889","doi":"https://doi.org/10.48550/arxiv.2605.23888","title":"GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction","display_name":"GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction","publication_year":2026,"publication_date":"2026-05-22","ids":{"openalex":"https://openalex.org/W7162308889","doi":"https://doi.org/10.48550/arxiv.2605.23888"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.23888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23888","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.2605.23888","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136938530","display_name":"Katharina Schmid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmid, Katharina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136935054","display_name":"Nicolas von L\u00fctzow","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"von L\u00fctzow, Nicolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136945841","display_name":"Jozef Hladk\u00fd","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hladk\u00fd, Jozef","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026634347","display_name":"Angela Dai","orcid":"https://orcid.org/0000-0002-6241-8782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Angela","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136979244","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":[]}],"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":0.8288999795913696,"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":0.8288999795913696,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05649999901652336,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.03220000118017197,"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/generative-grammar","display_name":"Generative grammar","score":0.6934999823570251},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.6047000288963318},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5471000075340271},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5023999810218811},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.484499990940094},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4681999981403351},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.41830000281333923},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4043999910354614}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7215999960899353},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6934999823570251},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6240000128746033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6089000105857849},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6047000288963318},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5471000075340271},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5023999810218811},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4681999981403351},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.41830000281333923},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4043999910354614},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4009999930858612},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2662999927997589}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.23888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23888","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.2605.23888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23888","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":[{"score":0.7380176782608032,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,24],"introduce":[1],"a":[2,19,33,82,93,141],"new":[3],"approach":[4],"to":[5,46,73,109,127],"high-fidelity":[6,145],"3D":[7,22,30,95],"scene":[8,26,48,75],"reconstruction":[9,17,27,150],"from":[10],"multi-view":[11,89,114],"RGB":[12],"images":[13],"that":[14,39,86,147],"tightly":[15],"couples":[16],"with":[18,98],"strong":[20,122],"generative":[21,59,100],"prior.":[23],"cast":[25],"as":[28,66],"conditional":[29],"generation":[31,45],"over":[32],"set":[34],"of":[35,57,103,125,137],"spatially-localized,":[36],"overlapping":[37],"chunks":[38],"together":[40],"tile":[41],"the":[42,53,74,99,110,121],"scene,":[43,111],"scaling":[44],"large":[47],"extents.":[49],"Crucially,":[50],"we":[51,63,71,80,143],"inherit":[52],"fidelity":[54],"and":[55,106],"completeness":[56],"state-of-the-art":[58],"shape":[60],"models":[61],"--":[62,69],"use":[64],"Trellis.2":[65,126],"an":[67],"example":[68],"which":[70],"generalize":[72],"level.":[76],"To":[77],"this":[78],"end,":[79],"propose":[81],"projection-based":[83],"conditioning":[84],"mechanism":[85],"lifts":[87],"posed":[88],"image":[90],"features":[91],"into":[92],"coherent":[94],"representation":[96],"aligned":[97],"model,":[101],"independent":[102],"view":[104],"ordering":[105],"spatially":[107],"anchored":[108],"yielding":[112],"high-fidelity,":[113],"consistent":[115],"generated":[116],"geometry.":[117],"This":[118],"enables":[119],"lifting":[120],"object-level":[123],"prior":[124],"multi-view,":[128],"scene-scale":[129],"generation,":[130],"producing":[131],"faithful,":[132],"editable":[133],"PBR":[134],"mesh":[135],"reconstructions":[136],"indoor":[138],"environments.":[139],"As":[140],"result,":[142],"obtain":[144],"results":[146],"outperform":[148],"cutting-edge":[149],"methods":[151],"by":[152],"16%.":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-26T00:00:00"}