{"id":"https://openalex.org/W4415346747","doi":"https://doi.org/10.1109/iccv51701.2025.02597","title":"Sat2City: 3D City Generation from a Single Satellite Image with Cascaded Latent Diffusion","display_name":"Sat2City: 3D City Generation from a Single Satellite Image with Cascaded Latent Diffusion","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415346747","doi":"https://doi.org/10.1109/iccv51701.2025.02597"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.02597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.04403","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012913113","display_name":"Tongyan Hua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tongyan Hua","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013246341","display_name":"Lutao Jiang","orcid":"https://orcid.org/0000-0002-1775-2765"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lutao Jiang","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101938761","display_name":"Ying-Cong Chen","orcid":"https://orcid.org/0000-0002-9565-8205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying-Cong Chen","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036391537","display_name":"Wufan Zhao","orcid":"https://orcid.org/0000-0002-0265-3465"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wufan Zhao","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China","institution_ids":[]}]}],"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":"27978","last_page":"27988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/rendering","display_name":"Rendering (computer graphics)","score":0.5706999897956848},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5296000242233276},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5184000134468079},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5060999989509583},{"id":"https://openalex.org/keywords/3d-city-models","display_name":"3D city models","score":0.45350000262260437},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4487000107765198},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.42329999804496765},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3903999924659729},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.3833000063896179},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991000175476074},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5706999897956848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5504999756813049},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5296000242233276},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5184000134468079},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5060999989509583},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.45350000262260437},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43540000915527344},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3140999972820282},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.30550000071525574},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28630000352859497},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2777897806","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3D modeling","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C41365986","wikidata":"https://www.wikidata.org/wiki/Q104153293","display_name":"Level of detail","level":2,"score":0.260699987411499}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv51701.2025.02597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.04403","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04403","pdf_url":"https://arxiv.org/pdf/2507.04403","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.04403","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04403","pdf_url":"https://arxiv.org/pdf/2507.04403","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1736313701","display_name":null,"funder_award_id":"42401567","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2258934996","display_name":null,"funder_award_id":"2024PF-1","funder_id":"https://openalex.org/F4320335792","funder_display_name":"Hubei Technological Innovation Special Fund"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335792","display_name":"Hubei Technological Innovation Special Fund","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,17],"generative":[3],"models":[4,153],"have":[5],"enabled":[6,93],"3D":[7,40,87,107,152,166,181],"urban":[8],"scene":[9],"generation":[10,195],"from":[11,54,110,183],"satellite":[12,111,186],"imagery,":[13,112],"unlocking":[14],"promising":[15],"applications":[16],"gaming,":[18],"digital":[19],"twins,":[20],"and":[21,132,157],"beyond.":[22],"However,":[23],"most":[24],"existing":[25,193],"methods":[26],"rely":[27],"heavily":[28],"on":[29,42,174],"neural":[30],"rendering":[31],"techniques,":[32],"which":[33],"hinder":[34],"their":[35],"ability":[36],"to":[37,48,123,192],"produce":[38],"detailed":[39,180],"structures":[41,109,182],"a":[43,66,114,161,184],"broader":[44],"scale,":[45],"largely":[46],"due":[47],"the":[49,71,146],"inherent":[50],"structural":[51],"ambiguity":[52],"derived":[53],"relatively":[55],"limited":[56],"2D":[57],"observations.":[58],"To":[59],"address":[60],"this":[61,175],"challenge,":[62],"we":[63,159],"propose":[64],"Sat2City,":[65],"novel":[67,86],"framework":[68,103,178],"that":[69,104],"synergizes":[70],"representational":[72],"capacity":[73],"of":[74,148,163],"sparse":[75],"voxel":[76],"grids":[77,127],"with":[78,154,169],"latent":[79,101],"diffusion":[80,102],"models,":[81],"tailored":[82],"specifically":[83],"for":[84,128,141],"our":[85,177],"city":[88,108,194],"dataset.":[89],"Our":[90],"approach":[91],"is":[92],"by":[94],"three":[95],"key":[96],"components:":[97],"(1)":[98],"A":[99],"cascaded":[100],"progressively":[105],"recovers":[106],"(2)":[113],"Re-Hash":[115],"operation":[116],"at":[117],"its":[118],"Variational":[119],"Autoencoder":[120],"(VAE)":[121],"bottleneck":[122],"compute":[124],"multi-scale":[125],"feature":[126],"stable":[129],"appearance":[130,143],"optimization":[131],"(3)":[133],"an":[134],"inverse":[135],"sampling":[136],"strategy":[137],"enabling":[138],"implicit":[139],"supervision":[140],"smooth":[142],"transitioning.To":[144],"overcome":[145],"challenge":[147],"collecting":[149],"real-world":[150],"city-scale":[151],"high-quality":[155],"geometry":[156],"appearance,":[158],"introduce":[160],"dataset":[162],"synthesized":[164],"large-scale":[165],"cities":[167],"paired":[168],"satellite-view":[170],"height":[171],"maps.":[172],"Validated":[173],"dataset,":[176],"generates":[179],"single":[185],"image,":[187],"achieving":[188],"superior":[189],"fidelity":[190],"compared":[191],"models.":[196]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-20T00:00:00"}
