{"id":"https://openalex.org/W7134825636","doi":"https://doi.org/10.1109/access.2026.3671877","title":"3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection","display_name":"3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7134825636","doi":"https://doi.org/10.1109/access.2026.3671877"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3671877","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3671877","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3671877","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kenta Ito","orcid":"https://orcid.org/0009-0002-1469-6662"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenta Ito","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan"],"raw_orcid":"https://orcid.org/0009-0002-1469-6662","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090580362","display_name":"Shiori Ueda","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shiori Ueda","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan"],"raw_orcid":"https://orcid.org/0009-0007-3820-6919","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030473547","display_name":"Shohei Mori","orcid":"https://orcid.org/0000-0003-0540-7312"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shohei Mori","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0540-7312","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016438638","display_name":"Junichi Sugano","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139663","display_name":"United Technologies Corporation (Poland)","ror":"https://ror.org/04gmtb593","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210139663"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Junichi Sugano","raw_affiliation_strings":["ViSCO Technologies Corporation, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ViSCO Technologies Corporation, Tokyo, Japan","institution_ids":["https://openalex.org/I4210139663"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025486711","display_name":"Hideyuki Adachi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139663","display_name":"United Technologies Corporation (Poland)","ror":"https://ror.org/04gmtb593","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210139663"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Hideyuki Adachi","raw_affiliation_strings":["ViSCO Technologies Corporation, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ViSCO Technologies Corporation, Tokyo, Japan","institution_ids":["https://openalex.org/I4210139663"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128672648","display_name":"Hideo Saito","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideo Saito","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2421-9862","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2222904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"37885","last_page":"37896"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7444000244140625,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7444000244140625,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10036","display_name":"Advanced Neural Network Applications","score":0.06030000001192093,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.026399999856948853,"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/pipeline","display_name":"Pipeline (software)","score":0.7926999926567078},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.7182000279426575},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5806999802589417},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5776000022888184},{"id":"https://openalex.org/keywords/automated-x-ray-inspection","display_name":"Automated X-ray inspection","score":0.5432999730110168},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.45320001244544983},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.40639999508857727},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.39750000834465027},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3749000132083893}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8428999781608582},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7926999926567078},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7610999941825867},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7271999716758728},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.7182000279426575},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5806999802589417},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5776000022888184},{"id":"https://openalex.org/C146920229","wikidata":"https://www.wikidata.org/wiki/Q2278114","display_name":"Automated X-ray inspection","level":4,"score":0.5432999730110168},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.45320001244544983},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.40639999508857727},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3749000132083893},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3028999865055084},{"id":"https://openalex.org/C2780527621","wikidata":"https://www.wikidata.org/wiki/Q7936593","display_name":"Visual control","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C164830781","wikidata":"https://www.wikidata.org/wiki/Q787330","display_name":"Automated optical inspection","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C17511633","wikidata":"https://www.wikidata.org/wiki/Q830694","display_name":"SMT placement equipment","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3671877","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3671877","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:09c7b898ac354fe4816fa663573d835b","is_oa":true,"landing_page_url":"https://doaj.org/article/09c7b898ac354fe4816fa663573d835b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 37885-37896 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3671877","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3671877","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46221810579299927,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G8156767572","display_name":null,"funder_award_id":"JPMJBS2409","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G8601827727","display_name":null,"funder_award_id":"JP24KJ1962","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8711217501","display_name":"EXC 2120: Integratives computerbasiertes Planen und Bauen f\u00fcr die Architektur","funder_award_id":"390831618","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"vision":[1],"systems":[2],"are":[3,23],"crucial":[4],"for":[5,28,92],"quality":[6],"control":[7],"in":[8,40,54,131],"manufacturing,":[9],"ensuring":[10],"that":[11,59,75,114],"products":[12],"meet":[13],"standards":[14],"through":[15],"automatic":[16],"in-line":[17],"visual":[18,72],"inspections.":[19],"While":[20],"reference":[21,86],"images":[22],"typically":[24],"used":[25],"as":[26],"benchmarks":[27],"comparison,":[29,93],"a":[30,71,84,108,117],"significant":[31],"challenge":[32],"arises":[33],"when":[34],"objects":[35,140],"arrive":[36],"at":[37],"inspection":[38,73,89],"points":[39],"misaligned":[41],"orientations.":[42],"This":[43],"misalignment":[44,97],"can":[45],"lead":[46],"to":[47,87,154],"erroneous":[48],"decisions":[49],"by":[50,134],"automated":[51],"systems,":[52],"resulting":[53],"false":[55],"positives":[56],"or":[57],"negatives":[58],"increase":[60],"waste":[61],"and":[62,105,141,150],"slow":[63],"production.":[64],"To":[65],"address":[66],"this":[67],"issue,":[68],"we":[69],"propose":[70],"pipeline":[74,81,147],"leverages":[76],"recent":[77],"machine-learning-based":[78],"approaches.":[79],"Our":[80],"virtually":[82],"reorients":[83],"3D":[85,102],"the":[88,96],"target\u2019s":[90],"orientation":[91],"effectively":[94],"addressing":[95],"issue.":[98],"Specifically,":[99],"it":[100,136],"integrates":[101],"Gaussian":[103],"Splatting":[104],"MASt3R,":[106],"enabling":[107],"robust":[109],"3D-based":[110],"defect":[111],"detection":[112],"system":[113],"uses":[115],"only":[116],"single":[118],"camera":[119],"sensor,":[120],"thereby":[121],"moving":[122],"beyond":[123],"traditional":[124],"2D":[125],"image-based":[126],"methods.We":[127],"validated":[128],"our":[129],"approach":[130],"real-world":[132],"scenarios":[133],"testing":[135],"on":[137],"20":[138],"synthetic":[139],"real":[142],"industrial":[143],"parts.":[144],"The":[145],"proposed":[146],"maintains":[148],"accuracy":[149],"processing":[151],"speed":[152],"comparable":[153],"those":[155],"of":[156],"existing":[157],"methods.":[158]},"counts_by_year":[],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2026-03-11T00:00:00"}
