{"id":"https://openalex.org/W7214764283","doi":"https://doi.org/10.3390/s26196173","title":"Semantic-Guided Adaptive Gaussian Segmentation","display_name":"Semantic-Guided Adaptive Gaussian Segmentation","publication_year":2026,"publication_date":"2026-09-29","ids":{"openalex":"https://openalex.org/W7214764283","doi":"https://doi.org/10.3390/s26196173","pmid":"https://pubmed.ncbi.nlm.nih.gov/42884373","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13667441"},"language":"en","primary_location":{"id":"doi:10.3390/s26196173","doi":"https://doi.org/10.3390/s26196173","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26196173","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/s26196173","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100678775","display_name":"Yinghan Zhou","orcid":"https://orcid.org/0009-0006-6366-9838","observed_orcids":["https://orcid.org/0009-0006-6366-9838","https://orcid.org/0009-0008-3467-8000"]},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghan Zhou","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047347318","display_name":"Fan Zhou","orcid":"https://orcid.org/0000-0003-3692-0530","observed_orcids":["https://orcid.org/0000-0003-3692-0530"]},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fan Zhou","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"],"raw_orcid":"https://orcid.org/0000-0003-3692-0530","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5047347318"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68805334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"19","first_page":"6173","last_page":"6173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.0007999999797903001,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/3d-gaussian-splatting","display_name":"3D Gaussian Splatting","score":0.9890000224113464},{"id":"https://openalex.org/keywords/3d-instance-segmentation","display_name":"3D instance segmentation","score":0.9710000157356262},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.734000027179718},{"id":"https://openalex.org/keywords/3d-consistency","display_name":"3D consistency","score":0.6610000133514404},{"id":"https://openalex.org/keywords/scannet","display_name":"ScanNet","score":0.3700000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560999989509583},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7203999757766724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7009999752044678},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5442000031471252},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5199999809265137},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5151000022888184},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47119998931884766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36719998717308044},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3190999925136566},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.26809999346733093},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s26196173","doi":"https://doi.org/10.3390/s26196173","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26196173","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13667441","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13667441/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13667441/pdf/sensors-26-06173.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmid:42884373","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42884373","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:7d3f9f25fc16492f894d6d90e0c24535","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/7d3f9f25fc16492f894d6d90e0c24535","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 26, Iss 19, p 6173 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s26196173","doi":"https://doi.org/10.3390/s26196173","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26196173","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2594519801","https://openalex.org/W3109908659","https://openalex.org/W4385318467","https://openalex.org/W4386065379","https://openalex.org/W4402715971","https://openalex.org/W4402727529","https://openalex.org/W4406526525","https://openalex.org/W4407433442","https://openalex.org/W4409606820","https://openalex.org/W4412417113","https://openalex.org/W4412451658","https://openalex.org/W4413145675","https://openalex.org/W4413146881","https://openalex.org/W4413156234","https://openalex.org/W4414198426","https://openalex.org/W4415913032","https://openalex.org/W7131133889","https://openalex.org/W7133197446"],"related_works":["https://openalex.org/W7124852792","https://openalex.org/W7213960441","https://openalex.org/W7214134873","https://openalex.org/W4416551492","https://openalex.org/W7214211676","https://openalex.org/W7170941552","https://openalex.org/W7117960837","https://openalex.org/W4413145675","https://openalex.org/W7163536518","https://openalex.org/W7128587963"],"abstract_inverted_index":{"3D":[0,19,47,109,156,169],"Gaussian":[1,48,67,86],"Splatting":[2],"(3DGS)":[3],"enables":[4],"real-time":[5],"photorealistic":[6],"scene":[7,189,202],"reconstruction,":[8],"yet":[9],"its":[10],"segmentation":[11,49,158],"tasks":[12],"suffer":[13],"from":[14],"two":[15,180],"critical":[16],"flaws:":[17],"poor":[18],"consistency":[20],"(e.g.,":[21],"blurred":[22],"instance":[23,106,113,157],"boundaries":[24],"and":[25,30,57,65,84,98,115,120,130,159,183,191,200],"unstable":[26],"cross-view":[27,95],"semantic":[28,58,63,82,99],"association)":[29],"insufficient":[31],"structural":[32],"awareness":[33],"near":[34],"ambiguous":[35],"object":[36],"boundaries.":[37,107],"To":[38],"address":[39],"these":[40],"issues,":[41],"this":[42],"paper":[43],"proposes":[44],"a":[45,72],"semantic-guided":[46],"framework.":[50],"We":[51,69],"first":[52],"process":[53],"multi-view":[54,102],"RGB":[55],"images":[56],"masks":[59],"to":[60,197],"generate":[61],"2D":[62],"codes":[64],"initial":[66],"parameters.":[68],"then":[70],"build":[71],"Gaussian-level":[73],"joint":[74],"representation":[75],"by":[76,151,160],"combining":[77],"flow-aligned":[78],"appearance":[79],"cues,":[80],"CLIP-derived":[81],"descriptors,":[83],"explicit":[85],"geometry.":[87],"Semantic-guided":[88],"adaptive":[89],"decomposition":[90],"identifies":[91],"boundary-sensitive":[92],"Gaussians":[93],"through":[94],"boundary":[96],"statistics":[97],"uncertainty,":[100],"while":[101,194],"voting":[103],"further":[104,206],"refines":[105],"Finally,":[108],"global":[110],"optimization":[111],"unifies":[112],"association":[114],"labeling.":[116],"Experiments":[117],"on":[118,137,178],"ScanNet":[119,139],"SPIn-NeRF":[121],"show":[122],"improved":[123],"results":[124,172],"under":[125],"the":[126,131,138,143,174,179],"reported":[127],"evaluation":[128],"protocol":[129],"stated":[132],"subset":[133],"definitions.":[134],"In":[135],"particular,":[136],"benchmark,":[140],"compared":[141],"with":[142],"evaluated":[144,181],"3DGS":[145],"baseline":[146],"InstanceGaussian,":[147],"SG-AGS":[148,177],"improves":[149],"mAcc@0.25":[150],"16.2":[152],"points":[153,162],"for":[154,163,187],"category-agnostic":[155],"25.6":[161],"text-query-based":[164],"open-vocabulary":[165],"labeling":[166],"of":[167,176],"segmented":[168],"instances.":[170],"These":[171],"support":[173],"usefulness":[175],"benchmarks":[182],"suggest":[184],"potential":[185],"value":[186],"object-level":[188],"querying":[190],"digital-twin":[192],"inspection,":[193],"broader":[195],"generalization":[196],"external":[198],"captures":[199],"other":[201],"domains":[203],"still":[204],"requires":[205],"validation.":[207]},"counts_by_year":[],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2026-09-30T00:00:00"}