{"id":"https://openalex.org/W7147547050","doi":"https://doi.org/10.1109/cw68232.2025.00027","title":"VoxelFlow: 2D Semantic Mask-Guided Voxel Flow for Open-Vocabulary 3D Instance Segmentation","display_name":"VoxelFlow: 2D Semantic Mask-Guided Voxel Flow for Open-Vocabulary 3D Instance Segmentation","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W7147547050","doi":"https://doi.org/10.1109/cw68232.2025.00027"},"language":null,"primary_location":{"id":"doi:10.1109/cw68232.2025.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cw68232.2025.00027","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 Cyberworlds (CW\uff09","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/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":["School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353513","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0002-0652-3297"},"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":"Huan Chen","raw_affiliation_strings":["School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132590908","display_name":"Jin Ma","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":"Jin Ma","raw_affiliation_strings":["School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"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":["School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132676494","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":["School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geospatial Engineering and Science, Sun Yat-sen University,Zhuhai,China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64008288,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7448999881744385,"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":0.7448999881744385,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.05689999833703041,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.03830000013113022,"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/voxel","display_name":"Voxel","score":0.8518000245094299},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7627000212669373},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7346000075340271},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.602400004863739},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.484499990940094},{"id":"https://openalex.org/keywords/geometric-data-analysis","display_name":"Geometric data analysis","score":0.4740999937057495},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.46810001134872437},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42980000376701355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3928999900817871}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.8518000245094299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7912999987602234},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7627000212669373},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7346000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7141000032424927},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.602400004863739},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5737000107765198},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C136520226","wikidata":"https://www.wikidata.org/wiki/Q302814","display_name":"Geometric data analysis","level":2,"score":0.4740999937057495},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3928999900817871},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.349700003862381},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.34279999136924744},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3337000012397766},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.32089999318122864},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2851000130176544}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cw68232.2025.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cw68232.2025.00027","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 Cyberworlds (CW\uff09","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6914129257202148,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4262066068","display_name":null,"funder_award_id":"42371343","funder_id":"https://openalex.org/F4320306080","funder_display_name":"Foundation for the National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306080","display_name":"Foundation for the National Institutes of Health","ror":"https://ror.org/00k86s890"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2160821342","https://openalex.org/W2594519801","https://openalex.org/W3216939881","https://openalex.org/W4214638047","https://openalex.org/W4214814555","https://openalex.org/W4312649925","https://openalex.org/W4383109105","https://openalex.org/W4386065742","https://openalex.org/W4386065874","https://openalex.org/W4386071493","https://openalex.org/W4386075561","https://openalex.org/W4386075597","https://openalex.org/W4386075819","https://openalex.org/W4386076523","https://openalex.org/W4390873101","https://openalex.org/W4390873312","https://openalex.org/W4402704512","https://openalex.org/W4402733570","https://openalex.org/W4402733574","https://openalex.org/W4402915908","https://openalex.org/W4403906550"],"related_works":[],"abstract_inverted_index":{"Open-vocabulary":[0],"3D":[1,30,73,98,148,167,224,237],"instance":[2,125,208,238],"segmentation":[3],"(OV3IS)":[4],"has":[5],"emerged":[6],"as":[7],"a":[8,34,63,112,146,176,197],"promising":[9],"field,":[10],"successfully":[11],"bridging":[12],"point":[13,51],"cloud":[14,52],"data":[15],"and":[16,45,53,85,92,117,130,170,188,201,214,235],"text":[17,202],"descriptions":[18],"through":[19,111],"intermediate":[20],"image":[21,54],"modalities.":[22],"However,":[23],"existing":[24],"approaches":[25],"often":[26],"rely":[27],"on":[28,165,212],"strong":[29],"clustering":[31],"priors":[32],"or":[33],"single,":[35],"isolated":[36],"2D":[37,69,90,106,143],"mask":[38,70],"branch,":[39],"which":[40],"typically":[41],"results":[42],"in":[43,89,136,156,232],"insufficient":[44],"inefficient":[46],"feature":[47],"interaction":[48],"between":[49],"the":[50,82],"domains.":[55],"To":[56],"address":[57],"these":[58,159,185],"limitations,":[59],"we":[60,141],"propose":[61],"VoxelFlow,":[62],"novel":[64],"framework":[65],"that":[66,217],"effectively":[67],"combines":[68],"semantics":[71],"with":[72,123,196],"geometric":[74,131,168],"features.":[75],"Our":[76],"core":[77],"insight":[78],"is":[79],"to":[80,95,150,204],"leverage":[81,93],"implicit":[83],"semantic":[84,129],"spatial":[86],"information":[87],"embedded":[88],"masks":[91,126,144,155,161,193],"them":[94],"replace":[96],"rigid":[97],"priors.":[99],"Specifically,":[100],"voxel":[101,154,160,182,192],"masks,":[102],"initially":[103],"derived":[104],"from":[105],"projections,":[107],"are":[108,162,194],"meticulously":[109],"refined":[110],"unique":[113],"two-stage":[114],"process:":[115],"growth":[116],"cross-frame":[118],"merging,":[119],"ensuring":[120],"precise":[121],"alignment":[122],"true":[124],"under":[127],"both":[128,233],"constraints.":[132],"The":[133],"methodology":[134],"unfolds":[135],"three":[137],"key":[138],"steps.":[139],"Firstly,":[140],"project":[142],"onto":[145],"voxelized":[147],"scene":[149],"establish":[151],"initial":[152],"seed":[153],"3D.":[157],"Secondly,":[158],"grown":[163],"based":[164],"local":[166],"features":[169],"progressively":[171],"merged":[172],"across":[173],"frames":[174],"using":[175],"dynamic":[177],"threshold,":[178],"yielding":[179],"robust":[180,223],"super":[181,191],"masks.":[183],"Finally,":[184],"semantically":[186],"consistent":[187],"geometrically":[189],"aligned":[190],"integrated":[195],"visual":[198],"language":[199],"model":[200],"embeddings":[203],"achieve":[205],"comprehensive":[206],"open-vocabulary":[207,236],"segmentation.":[209,239],"Extensive":[210],"experiments":[211],"ScanNet200":[213],"ScanNet++":[215],"demonstrate":[216],"VoxelFlow":[218],"not":[219],"only":[220],"significantly":[221],"outperforms":[222],"prior":[225],"baselines":[226],"but":[227],"also":[228],"achieves":[229],"superior":[230],"performance":[231],"class-agnostic":[234]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-04-02T00:00:00"}
