{"id":"https://openalex.org/W7151266136","doi":"https://doi.org/10.1109/icmla66185.2025.00052","title":"Rig-Aware 3D Reconstruction of Vehicle Undercarriages using Gaussian Splatting","display_name":"Rig-Aware 3D Reconstruction of Vehicle Undercarriages using Gaussian Splatting","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7151266136","doi":"https://doi.org/10.1109/icmla66185.2025.00052"},"language":null,"primary_location":{"id":"doi:10.1109/icmla66185.2025.00052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","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/A5102704792","display_name":"Nitin Kulkarni","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nitin Kulkarni","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133066999","display_name":"Akhil Devarashetti","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akhil Devarashetti","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133078156","display_name":"Charlie Cluss","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charlie Cluss","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068179126","display_name":"Livio Forte","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Livio Forte","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133146638","display_name":"Dan Buckmaster","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Buckmaster","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019702361","display_name":"Philip J. Schneider","orcid":"https://orcid.org/0000-0001-8740-809X"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Schneider","raw_affiliation_strings":["University at Buffalo,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo,Buffalo,NY,USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123455727","display_name":"Chunming Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I1314361725","display_name":"Buffalo Society of Natural Sciences","ror":"https://ror.org/01e3a4n81","country_code":"US","type":"archive","lineage":["https://openalex.org/I1314361725"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunming Qiao","raw_affiliation_strings":["ACV Auctions,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"ACV Auctions,Buffalo,NY,USA","institution_ids":["https://openalex.org/I1314361725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123517857","display_name":"Alina Vereshchaka","orcid":null},"institutions":[{"id":"https://openalex.org/I1314361725","display_name":"Buffalo Society of Natural Sciences","ror":"https://ror.org/01e3a4n81","country_code":"US","type":"archive","lineage":["https://openalex.org/I1314361725"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alina Vereshchaka","raw_affiliation_strings":["ACV Auctions,Buffalo,NY,USA"],"affiliations":[{"raw_affiliation_string":"ACV Auctions,Buffalo,NY,USA","institution_ids":["https://openalex.org/I1314361725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5102704792"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75880103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"338","last_page":"345"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11487","display_name":"Automotive and Human Injury Biomechanics","score":0.2371000051498413,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11487","display_name":"Automotive and Human Injury Biomechanics","score":0.2371000051498413,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.08869999647140503,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.057100001722574234,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/3d-reconstruction","display_name":"3D reconstruction","score":0.38519999384880066},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.32899999618530273},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.31369999051094055},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2865999937057495},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.28220000863075256}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.608299970626831},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.588699996471405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5656999945640564},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2538999915122986},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla66185.2025.00052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5367507338523865}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2000018820","https://openalex.org/W2033819227","https://openalex.org/W2137341062","https://openalex.org/W2144042618","https://openalex.org/W2151103935","https://openalex.org/W2471962767","https://openalex.org/W2905286037","https://openalex.org/W3034275286","https://openalex.org/W3166285241","https://openalex.org/W4200150166","https://openalex.org/W4221151978","https://openalex.org/W4256017923","https://openalex.org/W4385318467","https://openalex.org/W4390872507","https://openalex.org/W4391800855","https://openalex.org/W4404198699"],"related_works":[],"abstract_inverted_index":{"Inspecting":[0],"the":[1,45,48,60,75,109,121,143,155,160,182],"undercarriage":[2,29,46,189],"of":[3,44,59,111,123],"used":[4],"vehicles":[5],"is":[6,99],"a":[7,38,100,148],"labor-intensive":[8],"task":[9],"that":[10,36,170,191,201],"requires":[11],"inspectors":[12,66],"to":[13,20,41,69,79,107,164,186,207],"crouch":[14],"or":[15,83],"crawl":[16],"underneath":[17],"each":[18],"vehicle":[19,49],"thoroughly":[21],"examine":[22],"it.":[23],"Additionally,":[24],"online":[25],"buyers":[26],"rarely":[27],"see":[28],"photos.":[30],"We":[31,146],"present":[32],"an":[33,55],"end-to-end":[34],"pipeline":[35,104],"utilizes":[37],"three-camera":[39],"rig":[40],"capture":[42],"videos":[43],"as":[47],"drives":[50],"over":[51],"it,":[52],"and":[53,67,72,93,115,127,138,159,197],"produces":[54],"interactive":[56],"3D":[57,63],"model":[58,64],"undercarriage.":[61],"The":[62],"enables":[65],"customers":[68],"rotate,":[70],"zoom,":[71],"slice":[73],"through":[74],"undercarriage,":[76],"allowing":[77],"them":[78],"detect":[80],"rust,":[81],"leaks,":[82],"impact":[84],"damage":[85],"in":[86,193],"seconds,":[87],"thereby":[88],"improving":[89],"both":[90],"workplace":[91],"safety":[92],"buyer":[94],"confidence.":[95],"Our":[96,118,195],"primary":[97],"contribution":[98],"rig-aware":[101],"Structure-from-Motion":[102],"(SfM)":[103],"specifically":[105],"designed":[106],"overcome":[108],"challenges":[110,122],"wide-angle":[112,124],"lens":[113,125],"distortion":[114,126],"low-parallax":[116,128],"scenes.":[117],"method":[119],"overcomes":[120],"scenes":[129],"by":[130],"integrating":[131],"precise":[132],"camera":[133,144],"calibration,":[134],"synchronized":[135],"video":[136],"streams,":[137],"strong":[139],"geometric":[140],"priors":[141],"from":[142],"rig.":[145],"use":[147],"constrained":[149],"matching":[150],"strategy":[151],"with":[152,174],"learned":[153],"components,":[154],"DISK":[156],"feature":[157],"extractor,":[158],"attention-based":[161],"LightGlue":[162],"matcher":[163],"generate":[165,187],"high-quality":[166],"sparse":[167],"point":[168,179],"clouds":[169,180],"are":[171,205],"often":[172],"unattainable":[173],"standard":[175],"SfM":[176],"pipelines.":[177],"These":[178],"seed":[181],"Gaussian":[183],"splatting":[184],"process":[185],"photorealistic":[188],"models":[190],"render":[192],"real-time.":[194],"experiments":[196],"ablation":[198],"studies":[199],"demonstrate":[200],"our":[202],"design":[203],"choices":[204],"essential":[206],"achieve":[208],"state-of-the-art":[209],"quality.":[210]},"counts_by_year":[],"updated_date":"2026-04-09T06:08:40.794217","created_date":"2026-04-08T00:00:00"}