{"id":"https://openalex.org/W7125025029","doi":"https://doi.org/10.1109/jiot.2026.3655384","title":"Context-Aware RandLA-Net: An Enhanced Architecture for Large-Scale Point Cloud Semantic Segmentation","display_name":"Context-Aware RandLA-Net: An Enhanced Architecture for Large-Scale Point Cloud Semantic Segmentation","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7125025029","doi":"https://doi.org/10.1109/jiot.2026.3655384"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3655384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3655384","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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 Internet of Things Journal","raw_type":"journal-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":null,"display_name":"Jin Sun","orcid":"https://orcid.org/0000-0002-1074-8202"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Sun","raw_affiliation_strings":["School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1074-8202","affiliations":[{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123408332","display_name":"Yuemin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuemin Li","raw_affiliation_strings":["School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028315682","display_name":"Haowei Huang","orcid":"https://orcid.org/0000-0002-7152-3488"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haowei Huang","raw_affiliation_strings":["School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123445553","display_name":"Yue Yin","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":"Yue Yin","raw_affiliation_strings":["Department of Information and Computer Science, Keio University, Yokohama, Japan"],"raw_orcid":"https://orcid.org/0009-0005-5685-0367","affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tiantian Tang","orcid":"https://orcid.org/0000-0002-8596-1227"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiantian Tang","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8596-1227","affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123372793","display_name":"Haitao Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Zhao","raw_affiliation_strings":["School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3539-3532","affiliations":[{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027367677","display_name":"Guan Gui","orcid":"https://orcid.org/0000-0003-3888-2881"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guan Gui","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-3888-2881","affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09836758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"11","first_page":"22646","last_page":"22657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8341000080108643,"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":0.8341000080108643,"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":0.039900001138448715,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.027699999511241913,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6959999799728394},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6952999830245972},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6873999834060669},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6474000215530396},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5389000177383423},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5253999829292297},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5235000252723694},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.436599999666214},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.40059998631477356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8180999755859375},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6959999799728394},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6952999830245972},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6873999834060669},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6474000215530396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5834000110626221},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5389000177383423},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5253999829292297},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5235000252723694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.39879998564720154},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.36809998750686646},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36489999294281006},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3095000088214874},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2687000036239624},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.25540000200271606},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3655384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3655384","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7642557621002197,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3099103210","display_name":null,"funder_award_id":"GKZD010084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3766218786","display_name":null,"funder_award_id":"62203231","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"semantic":[3,55,249],"segmentation":[4,45,127,250],"of":[5,29,43,70,222,233],"large-scale":[6,30,246],"point":[7,31,71,247],"clouds":[8],"has":[9,48],"garnered":[10],"significant":[11],"attention":[12,107,115],"due":[13],"to":[14,66,146],"its":[15],"critical":[16],"role":[17],"in":[18,52,133],"3D":[19,152,192],"scene":[20],"understanding.":[21],"However,":[22],"the":[23,40,68,97,126,131,141,156,206],"inherent":[24],"complexity":[25],"and":[26,102,113,124,168,194,209,224,226,235,241],"uneven":[27],"distribution":[28],"clouds,":[32],"coupled":[33],"with":[34,199],"substantial":[35],"inter-class":[36],"similarity,":[37],"significantly":[38],"hinder":[39],"discriminative":[41],"power":[42],"existing":[44,239],"approaches.":[46],"RandLA-Net":[47],"shown":[49],"strong":[50],"capabilities":[51],"directly":[53],"inferring":[54],"information.":[56],"Building":[57],"upon":[58],"this":[59],"foundation,":[60],"we":[61],"proposed":[62],"three":[63],"redesigned":[64],"modules":[65],"improve":[67],"accuracy":[69],"cloud":[72,248],"segmentation:":[73],"a":[74,80,87,177],"Local":[75],"Contextual":[76,82,88],"Feature":[77,83,89],"(LCF)":[78],"module,":[79],"Global":[81],"(GCF)":[84],"module":[85,95,143,173],"and,":[86],"Enhancement":[90],"(CFE)":[91],"module.":[92],"The":[93,171],"LCF":[94],"preserves":[96],"local":[98,121,139,167],"spatial":[99,157],"encoding":[100],"unit":[101],"introduces":[103],"an":[104],"improved":[105],"dual":[106],"mechanism":[108],"that":[109,214],"independently":[110],"computes":[111],"geometric":[112],"feature-based":[114],"scores.":[116],"This":[117],"facilitates":[118],"more":[119],"effective":[120],"feature":[122,163,182,196],"aggregation":[123],"overcomes":[125],"artifacts":[128],"caused":[129],"by":[130,154,184],"difficulty":[132],"distinguishing":[134],"similar":[135],"classes.":[136],"To":[137],"complement":[138],"representations,":[140],"GCF":[142],"is":[144,174],"integrated":[145],"capture":[147],"scene-level":[148],"semantics":[149],"across":[150,251],"all":[151],"points":[153],"using":[155],"position":[158],"volume":[159],"ratio,":[160],"thereby":[161],"addressing":[162],"extraction":[164],"from":[165,189],"both":[166,190],"global":[169,200],"perspectives.":[170],"CFE":[172],"designed":[175],"as":[176],"plug-and-play":[178],"component,":[179],"which":[180],"enhances":[181],"representations":[183],"integrating":[185],"richer":[186],"contextual":[187],"cues":[188],"explicit":[191],"geometry":[193],"implicit":[195],"spaces,":[197],"along":[198],"bilinear":[201],"interactions.":[202],"Comprehensive":[203],"experiments":[204],"on":[205],"S3DIS":[207],"(indoor)":[208],"Semantic3D":[210],"(outdoor)":[211],"datasets":[212],"show":[213],"our":[215],"method":[216],"attains":[217],"Overall":[218],"Accuracy":[219],"(OA)":[220],"scores":[221,232],"89.8%":[223],"95.3%,":[225],"mean":[227],"Intersection":[228],"over":[229],"Union":[230],"(mIoU)":[231],"73.3%":[234],"78.0%,":[236],"respectively,":[237],"outperforming":[238],"methods":[240],"providing":[242],"new":[243],"perspectives":[244],"for":[245],"diverse":[252],"environments.":[253]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-21T00:00:00"}
