{"id":"https://openalex.org/W7138327170","doi":"https://doi.org/10.1609/aaai.v40i12.37931","title":"SGS-3D: High-Fidelity 3D Instance Segmentation via Reliable Semantic Mask Splitting and Growing","display_name":"SGS-3D: High-Fidelity 3D Instance Segmentation via Reliable Semantic Mask Splitting and Growing","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138327170","doi":"https://doi.org/10.1609/aaai.v40i12.37931"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i12.37931","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37931","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37931/41893","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37931/41893","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005147189","display_name":"Chaolei Wang","orcid":"https://orcid.org/0000-0003-0205-1381"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaolei Wang","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129715461","display_name":"Yang Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Luo","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129737917","display_name":"Jing Du","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jing Du","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129737936","display_name":"Siyu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I161346416","display_name":"Jimei University","ror":"https://ror.org/03hknyb50","country_code":"CN","type":"education","lineage":["https://openalex.org/I161346416"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Chen","raw_affiliation_strings":["Jimei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jimei University","institution_ids":["https://openalex.org/I161346416"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129710592","display_name":"Yiping Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Chen","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129716283","display_name":"Ting Han","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Han","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.1111,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97777778,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"40","issue":"12","first_page":"9684","last_page":"9692"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5095999836921692,"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":0.5095999836921692,"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":0.23549999296665192,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.07129999995231628,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/segmentation","display_name":"Segmentation","score":0.8069000244140625},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6650999784469604},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.6154000163078308},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.573199987411499},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5134000182151794},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46219998598098755},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4366999864578247},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.41510000824928284}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8069000244140625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7590000033378601},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6650999784469604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6370999813079834},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6154000163078308},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5735999941825867},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.573199987411499},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5134000182151794},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.41510000824928284},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3959999978542328},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.31679999828338623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.2660999894142151}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i12.37931","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37931","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37931/41893","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i12.37931","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37931","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37931/41893","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138327170.pdf","grobid_xml":"https://content.openalex.org/works/W7138327170.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"3D":[1,12,16,61,142,159],"instance":[2,17,62],"segmentation":[3,18,63,102,201],"is":[4],"crucial":[5],"for":[6,59,128],"high-quality":[7],"scene":[8],"understanding":[9],"in":[10,180],"the":[11,36,88,122,139,158,163,181],"vision":[13],"domain.":[14],"However,":[15],"based":[19],"on":[20,96,191],"2D-to-3D":[21],"lifting":[22,37],"approaches":[23,92],"struggle":[24],"to":[25,31,145],"produce":[26],"precise":[27],"instance-level":[28],"segmentation,":[29],"due":[30],"accumulated":[32],"errors":[33],"introduced":[34],"during":[35],"process":[38],"from":[39,208],"ambiguous":[40,74,149],"semantic":[41,114,129,155,184],"guidance":[42],"and":[43,54,72,80,100,115,147,176,194,203,222],"insufficient":[44],"depth":[45],"constraints.":[46],"To":[47],"tackle":[48],"these":[49],"challenges,":[50],"we":[51,131,166],"propose":[52],"Splitting":[53],"Growing":[55],"reliable":[56,154],"Semantic":[57],"mask":[58,134],"high-fidelity":[60,212],"(SGS-3D),":[64],"a":[65,107,133],"novel":[66],"\"split-then-grow\"":[67],"framework":[68],"that":[69,93,111,137,197],"first":[70],"purifies":[71],"splits":[73],"lifted":[75,98],"masks":[76,99,207],"using":[77],"geometric":[78,116,164],"primitives,":[79],"then":[81],"grows":[82],"them":[83],"into":[84],"complete":[85],"instances":[86,170,214],"within":[87],"scene.":[89],"Unlike":[90],"existing":[91],"directly":[94],"rely":[95],"raw":[97],"sacrifice":[101],"accuracy,":[103],"SGS-3D":[104,198],"serves":[105],"as":[106],"training-free":[108],"refinement":[109],"method":[110],"jointly":[112],"fuses":[113],"information,":[117],"enabling":[118],"effective":[119],"cooperation":[120],"between":[121,186],"two":[123],"levels":[124],"of":[125,141,183],"representation.":[126],"Specifically,":[127],"guidance,":[130],"introduce":[132],"filtering":[135],"strategy":[136],"leverages":[138],"co-occurrence":[140],"geometry":[143],"primitives":[144],"identify":[146],"remove":[148],"masks,":[150],"thereby":[151],"ensuring":[152],"more":[153],"consistency":[156],"with":[157],"object":[160,169,213],"instances.":[161],"For":[162],"refinement,":[165],"construct":[167],"fine-grained":[168],"by":[171],"exploiting":[172],"both":[173],"spatial":[174],"continuity":[175],"high-level":[177],"features,":[178],"particularly":[179],"case":[182],"ambiguity":[185],"distinct":[187],"objects.":[188],"Experimental":[189],"results":[190],"ScanNet200,":[192],"ScanNet++,":[193],"KITTI-360":[195],"demonstrate":[196],"substantially":[199],"improves":[200],"accuracy":[202],"robustness":[204],"against":[205],"inaccurate":[206],"pre-trained":[209],"models,":[210],"yielding":[211],"while":[215],"maintaining":[216],"strong":[217],"generalization":[218],"across":[219],"diverse":[220],"indoor":[221],"outdoor":[223],"environments.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-13T07:54:00.901334","created_date":"2026-03-18T00:00:00"}
