{"id":"https://openalex.org/W4368408201","doi":"https://doi.org/10.1145/3576841.3585924","title":"sat2pc: Generating Building Roof's Point Cloud from a Single 2D Satellite Images","display_name":"sat2pc: Generating Building Roof's Point Cloud from a Single 2D Satellite Images","publication_year":2023,"publication_date":"2023-05-04","ids":{"openalex":"https://openalex.org/W4368408201","doi":"https://doi.org/10.1145/3576841.3585924"},"language":"en","primary_location":{"id":"doi:10.1145/3576841.3585924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3576841.3585924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056482171","display_name":"Yoones Rezaei","orcid":"https://orcid.org/0000-0001-6706-4517"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yoones Rezaei","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, United States of America"],"raw_orcid":"https://orcid.org/0000-0001-6706-4517","affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, United States of America","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100650753","display_name":"Stephen Lee","orcid":"https://orcid.org/0000-0001-9022-4259"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Lee","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, United States of America"],"raw_orcid":"https://orcid.org/0000-0001-9022-4259","affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, United States of America","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.224,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48482484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"221","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9947999715805054,"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/computer-science","display_name":"Computer science","score":0.7928752899169922},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7732986211776733},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7643770575523376},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.6427491903305054},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5132181644439697},{"id":"https://openalex.org/keywords/3d-city-models","display_name":"3D city models","score":0.4990525245666504},{"id":"https://openalex.org/keywords/roof","display_name":"Roof","score":0.498457670211792},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4191191792488098},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4180770516395569},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37965238094329834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3204723000526428},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.1835770308971405},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09919646382331848},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.09503105282783508}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7928752899169922},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7732986211776733},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7643770575523376},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.6427491903305054},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5132181644439697},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.4990525245666504},{"id":"https://openalex.org/C2776748203","wikidata":"https://www.wikidata.org/wiki/Q83180","display_name":"Roof","level":2,"score":0.498457670211792},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4191191792488098},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4180770516395569},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37965238094329834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3204723000526428},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.1835770308971405},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09919646382331848},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.09503105282783508},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3576841.3585924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3576841.3585924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2012101600","https://openalex.org/W2038771072","https://openalex.org/W2066483145","https://openalex.org/W2096763839","https://openalex.org/W2115579991","https://openalex.org/W2194775991","https://openalex.org/W2519517723","https://openalex.org/W2560722161","https://openalex.org/W2603429625","https://openalex.org/W2603777577","https://openalex.org/W2771852828","https://openalex.org/W2952424961","https://openalex.org/W2982131530","https://openalex.org/W2997088169","https://openalex.org/W2997343139","https://openalex.org/W3017740917","https://openalex.org/W3035003562","https://openalex.org/W3035014292","https://openalex.org/W3036406207","https://openalex.org/W3081162165","https://openalex.org/W3122797415","https://openalex.org/W3203230094","https://openalex.org/W6888505029"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W2573957257","https://openalex.org/W2948902595","https://openalex.org/W963789794","https://openalex.org/W3090729437"],"abstract_inverted_index":{"Three-dimensional":[0],"(3D)":[1],"urban":[2],"models":[3,63],"have":[4],"gained":[5],"interest":[6],"because":[7],"of":[8,95,110],"their":[9],"applications":[10],"in":[11,57,136,186],"many":[12,55],"use-cases":[13],"such":[14],"as":[15],"disaster":[16],"management,":[17],"energy":[18],"management":[19],"and":[20,49,89,130,145,152,201],"solar":[21],"potential":[22],"analysis.":[23],"However,":[24],"generating":[25],"these":[26,66],"3D":[27,62,138,188],"representations":[28],"requires":[29],"LiDAR":[30],"data,":[31],"which":[32],"is":[33,40,80],"usually":[34],"expensive":[35],"to":[36,74],"collect.":[37],"Because":[38],"it":[39],"expensive,":[41],"the":[42,58,78,107,142,167,182,194],"lidar":[43,67],"data":[44,68,79],"are":[45,50,69,86],"not":[46,51],"frequently":[47,90],"updated":[48],"widely":[52],"available":[53,88],"for":[54],"regions":[56],"US.":[59],"As":[60],"such,":[61],"based":[64],"on":[65,156],"either":[70],"outdated":[71],"or":[72],"limited":[73],"those":[75],"locations":[76],"where":[77],"available.":[81],"In":[82],"contrast,":[83],"satellite":[84,118],"images":[85],"freely":[87],"updated.":[91],"To":[92],"take":[93],"advantage":[94],"this":[96],"availability,":[97],"we":[98,175,191],"propose":[99],"sat2pc,":[100],"a":[101,111,115,137,157],"deep":[102],"learning-based":[103],"approach":[104],"that":[105,140,164,177,193],"predicts":[106],"point":[108,196],"cloud":[109,197],"building":[112,158],"roof":[113,159],"from":[114],"single":[116],"2D":[117],"image.":[119],"Our":[120,161],"technique":[121],"integrates":[122],"two":[123],"different":[124],"loss":[125],"functions,":[126],"namely":[127],"Chamfer":[128],"Distance":[129,133],"Earth":[131],"Mover's":[132],"loss,":[134],"resulting":[135,185],"output":[139],"balances":[141],"overall":[143,183],"structure":[144],"detail.":[146],"We":[147],"extensively":[148],"evaluate":[149],"our":[150,178],"model":[151],"perform":[153],"ablation":[154],"studies":[155],"dataset.":[160],"results":[162],"show":[163,176,192],"sat2pc":[165],"outperforms":[166],"existing":[168],"baselines":[169],"by":[170],"at":[171],"least":[172],"18.6%.":[173],"Moreover,":[174],"refinement":[179],"module":[180],"improves":[181],"performance,":[184],"fine-grained":[187],"output.":[189],"Finally,":[190],"predicted":[195],"captures":[198],"more":[199],"detail":[200],"geometric":[202],"characteristics":[203],"than":[204],"other":[205],"baselines.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}