{"id":"https://openalex.org/W7162562467","doi":"https://doi.org/10.1109/icmre69538.2026.11533911","title":"SwarmGaussian: Distributed 3D Gaussian Splatting for High Fidelity Aerial Scene Reconstruction","display_name":"SwarmGaussian: Distributed 3D Gaussian Splatting for High Fidelity Aerial Scene Reconstruction","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7162562467","doi":"https://doi.org/10.1109/icmre69538.2026.11533911"},"language":"en","primary_location":{"id":"doi:10.1109/icmre69538.2026.11533911","doi":"https://doi.org/10.1109/icmre69538.2026.11533911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmre69538.2026.11533911","pdf_url":null,"source":{"id":"https://openalex.org/S7407086286","display_name":"International Conference on Mechatronics and Robotics Engineering (ICMRE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 12th International Conference on Mechatronics and Robotics Engineering (ICMRE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5077520782","display_name":"Yao Yeboah","orcid":"https://orcid.org/0000-0002-1116-0670","observed_orcids":["https://orcid.org/0000-0002-1116-0670"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao Yeboah","raw_affiliation_strings":["Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095909877","display_name":"Joseph Teye Ignatius Buertey","orcid":"https://orcid.org/0000-0002-1483-4685","observed_orcids":["https://orcid.org/0000-0002-1483-4685"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joseph Teye Ignatius Buertey","raw_affiliation_strings":["Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137163046","display_name":"Kwabena Agyapong-Kodua","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwabena Agyapong-Kodua","raw_affiliation_strings":["Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Computing, Pentecost University,Faculty of Engineering,Accra,Ghana","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029669305","display_name":"Zeyad Farisi","orcid":"https://orcid.org/0000-0002-4602-9402","observed_orcids":["https://orcid.org/0000-0002-4602-9402","https://orcid.org/0000-0001-7747-320X","https://orcid.org/0000-0003-3533-9517"]},"institutions":[{"id":"https://openalex.org/I23075662","display_name":"Taibah University","ror":"https://ror.org/01xv1nn60","country_code":"SA","type":"education","lineage":["https://openalex.org/I23075662"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Zeyad Farisi","raw_affiliation_strings":["Applied College, Taibah University,Medina City,Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied College, Taibah University,Medina City,Saudi Arabia","institution_ids":["https://openalex.org/I23075662"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4443,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80603448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"289","last_page":"295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7670999765396118,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7670999765396118,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.20589999854564667,"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":0.01119999960064888,"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/3d-gaussian-splatting","display_name":"3D Gaussian Splatting","score":0.9639999866485596},{"id":"https://openalex.org/keywords/multi-view-video","display_name":"multi-view video","score":0.7870000004768372},{"id":"https://openalex.org/keywords/space-partitioning","display_name":"spatial partitioning","score":0.9409999847412109},{"id":"https://openalex.org/keywords/structural-assessment","display_name":"structural assessment","score":0.5609999895095825},{"id":"https://openalex.org/keywords/surveying","display_name":"surveying","score":0.4650000035762787},{"id":"https://openalex.org/keywords/non-lambertian-surfaces","display_name":"non-Lambertian surfaces","score":0.8220000267028809}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796000003814697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6513000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6240000128746033},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3375000059604645},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.26829999685287476},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.25679999589920044},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C133214962","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial photography","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.25029999017715454},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmre69538.2026.11533911","doi":"https://doi.org/10.1109/icmre69538.2026.11533911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmre69538.2026.11533911","pdf_url":null,"source":{"id":"https://openalex.org/S7407086286","display_name":"International Conference on Mechatronics and Robotics Engineering (ICMRE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 12th International Conference on Mechatronics and Robotics Engineering (ICMRE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2019400639","https://openalex.org/W2048710758","https://openalex.org/W2094447963","https://openalex.org/W2117228865","https://openalex.org/W2139331573","https://openalex.org/W2151103935","https://openalex.org/W2156598602","https://openalex.org/W2471962767","https://openalex.org/W2519683295","https://openalex.org/W2775929773","https://openalex.org/W2951856026","https://openalex.org/W2962793285","https://openalex.org/W2982169158","https://openalex.org/W2990957769","https://openalex.org/W3034530552","https://openalex.org/W3035172746","https://openalex.org/W3109585842","https://openalex.org/W3199654312","https://openalex.org/W4306157941","https://openalex.org/W4312280420","https://openalex.org/W4312546206","https://openalex.org/W4313031684","https://openalex.org/W4385318467","https://openalex.org/W4386501079","https://openalex.org/W4399801254","https://openalex.org/W4404191272","https://openalex.org/W4413145241","https://openalex.org/W4415077292","https://openalex.org/W4415502379"],"related_works":["https://openalex.org/W7213996023","https://openalex.org/W4403751223","https://openalex.org/W4416751085","https://openalex.org/W4415108968","https://openalex.org/W7161967136","https://openalex.org/W7140700682","https://openalex.org/W7164157711","https://openalex.org/W4413925950","https://openalex.org/W7131619143","https://openalex.org/W7208756856"],"abstract_inverted_index":{"The":[0,128],"ability":[1],"to":[2,39,146],"reconstruct":[3],"high-fidelity":[4,176],"3D":[5,66,187,195],"assets":[6,196],"from":[7,119],"video":[8,121],"has":[9],"long":[10],"held":[11],"promise":[12,59],"for":[13,92,112,198],"applications":[14,200],"such":[15,201],"as":[16,202],"inspection,":[17,205],"structural":[18,203],"assessment,":[19,204],"and":[20,49,76,82,114,138,151,160,175,206],"surveying.":[21,208],"While":[22],"traditional":[23],"photogrammetry":[24],"techniques":[25],"have":[26,56],"demonstrated":[27],"strong":[28],"performance":[29],"in":[30,60],"controlled":[31],"settings,":[32],"they":[33],"often":[34],"lack":[35],"the":[36,80],"robustness":[37],"required":[38],"handle":[40],"complex":[41,156],"scene":[42,54,117,133],"characteristics,":[43],"including":[44],"non-Lambertian":[45],"surfaces,":[46],"reflective":[47],"materials,":[48],"non-diffuse":[50],"appearance.":[51],"Recent":[52],"neural":[53],"representations":[55],"shown":[57],"significant":[58],"addressing":[61],"these":[62],"challenges.":[63],"In":[64,104],"particular,":[65],"Gaussian":[67,86,136],"Splatting":[68],"achieves":[69],"an":[70],"effective":[71],"balance":[72],"between":[73],"reconstruction":[74,118,167,189],"quality":[75],"rendering":[77],"efficiency.":[78],"However,":[79],"explicit":[81],"memory-intensive":[83],"nature":[84],"of":[85,125,144],"primitives":[87],"makes":[88],"existing":[89],"approaches":[90],"prohibitive":[91],"large-scale":[93,115,207],"reconstruction,":[94],"especially":[95],"when":[96],"data":[97],"is":[98],"captured":[99,122],"across":[100,168,190],"multiple":[101,169],"aerial":[102,116,126,191],"platforms.":[103],"this":[105],"work,":[106],"we":[107],"present":[108],"SwarmGaussian,":[109],"a":[110],"framework":[111],"incremental":[113],"multi-view":[120],"by":[123],"swarms":[124],"vehicles.":[127],"proposed":[129],"approach":[130],"integrates":[131],"semantic":[132],"clustering,":[134],"depthguided":[135],"optimisation,":[137],"spatial":[139],"partitioning":[140],"with":[141],"adaptive":[142],"levels":[143],"detail":[145],"enable":[147],"efficient":[148,185],"distributed":[149,186],"optimisation":[150],"scalable":[152],"reconstruction.":[153],"By":[154],"decomposing":[155],"scenes":[157],"into":[158],"semantically":[159],"spatially":[161],"coherent":[162],"subregions,":[163],"SwarmGaussian":[164,183],"supports":[165],"parallel":[166],"agents":[170],"while":[171],"maintaining":[172],"global":[173],"consistency":[174],"visual":[177],"quality.":[178],"Experimental":[179],"results":[180],"demonstrate":[181],"that":[182],"enables":[184],"Gaussian-based":[188],"swarms,":[192],"producing":[193],"high-quality":[194],"suitable":[197],"downstream":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-05-28T00:00:00"}