{"id":"https://openalex.org/W4390041998","doi":"https://doi.org/10.48550/arxiv.2312.11880","title":"Point Cloud Segmentation Using Transfer Learning with RandLA-Net: A Case Study on Urban Areas","display_name":"Point Cloud Segmentation Using Transfer Learning with RandLA-Net: A Case Study on Urban Areas","publication_year":2023,"publication_date":"2023-12-19","ids":{"openalex":"https://openalex.org/W4390041998","doi":"https://doi.org/10.48550/arxiv.2312.11880"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2312.11880","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.11880","pdf_url":"https://arxiv.org/pdf/2312.11880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2312.11880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006904112","display_name":"Alperen Enes Bayar","orcid":"https://orcid.org/0009-0001-8921-6179","observed_orcids":["https://orcid.org/0009-0001-8921-6179"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I4210091955","display_name":"Eskisehir Technical University","ror":"https://ror.org/00gcgqv39","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210091955"]}],"countries":["CN","TR"],"is_corresponding":false,"raw_author_name":"Bayar, Alperen Enes","raw_affiliation_strings":["Eskisehir Technical University","Huawei Turkey R&D Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eskisehir Technical University","institution_ids":["https://openalex.org/I4210091955"]},{"raw_affiliation_string":"Huawei Turkey R&D Center","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062328475","display_name":"Ufuk Uyan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Uyan, Ufuk","raw_affiliation_strings":["Huawei Turkey R&D Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Turkey R&D Center","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054173754","display_name":"Elif Toprak","orcid":"https://orcid.org/0000-0002-1597-8728","observed_orcids":["https://orcid.org/0000-0002-1597-8728"]},"institutions":[{"id":"https://openalex.org/I100072489","display_name":"Yeditepe University","ror":"https://ror.org/025mx2575","country_code":"TR","type":"education","lineage":["https://openalex.org/I100072489"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","TR"],"is_corresponding":false,"raw_author_name":"Toprak, Elif","raw_affiliation_strings":["Huawei Turkey R&D Center","Yeditepe University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Turkey R&D Center","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Yeditepe University","institution_ids":["https://openalex.org/I100072489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070823844","display_name":"Cao Yuheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuheng, Cao","raw_affiliation_strings":["Huawei Technologies"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093547856","display_name":"Tang Juncheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juncheng, Tang","raw_affiliation_strings":["Huawei Technologies"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032732638","display_name":"Ahmet Alp K\u0131nd\u0131ro\u011flu","orcid":"https://orcid.org/0000-0002-5299-1956","observed_orcids":["https://orcid.org/0000-0002-5299-1956"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kindiroglu, Ahmet Alp","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7720000147819519,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"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":0.7720000147819519,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.15649999678134918,"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/T12698","display_name":"3D Modeling in Geospatial Applications","score":0.031300000846385956,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/point-cloud-segmentation","display_name":"point cloud segmentation","score":0.8489999771118164},{"id":"https://openalex.org/keywords/randla-net","display_name":"RandLA-Net","score":0.9580000042915344},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.9739999771118164},{"id":"https://openalex.org/keywords/urban-point-clouds","display_name":"urban point clouds","score":0.7480000257492065},{"id":"https://openalex.org/keywords/limited-labeled-data","display_name":"limited labeled data","score":0.7670000195503235},{"id":"https://openalex.org/keywords/3d-semantic-segmentation","display_name":"3D semantic segmentation","score":0.6520000100135803},{"id":"https://openalex.org/keywords/chinese-cities","display_name":"Chinese cities","score":0.7279999852180481},{"id":"https://openalex.org/keywords/chengdu","display_name":"Chengdu","score":0.7509999871253967},{"id":"https://openalex.org/keywords/shenzhen","display_name":"Shenzhen","score":1.0}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8409245014190674},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7952167987823486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067803144454956},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6297118663787842},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6157611608505249},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5993161201477051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5046161413192749},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4637821912765503},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45792657136917114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44445502758026123},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42441874742507935},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.41963496804237366},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.41557595133781433},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38861918449401855},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.23489511013031006},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2312.11880","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.11880","pdf_url":"https://arxiv.org/pdf/2312.11880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2312.11880","doi":"https://doi.org/10.48550/arxiv.2312.11880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2312.11880","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2312.11880","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.11880","pdf_url":"https://arxiv.org/pdf/2312.11880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7646999955177307,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390041998.pdf","grobid_xml":"https://content.openalex.org/works/W4390041998.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4406728838","https://openalex.org/W4306399487","https://openalex.org/W4309122661","https://openalex.org/W4404692666","https://openalex.org/W4400924454","https://openalex.org/W3200344780","https://openalex.org/W7220547527","https://openalex.org/W4413980323","https://openalex.org/W4389681952","https://openalex.org/W4415402499"],"abstract_inverted_index":{"Urban":[0,95],"environments":[1],"are":[2],"characterized":[3],"by":[4],"complex":[5],"structures":[6],"and":[7,59,96],"diverse":[8],"features,":[9],"making":[10],"accurate":[11,120],"segmentation":[12,39,67,121,177],"of":[13,29,40,74,129,174,183],"point":[14,42,143,165,175],"cloud":[15,43,144,166,176],"data":[16,44,76,156],"a":[17,23,31,160],"challenging":[18],"task.":[19],"This":[20],"paper":[21],"presents":[22],"comprehensive":[24],"study":[25,49],"on":[26,51],"the":[27,37,71,89,93,112,115,127,130,172,181],"application":[28],"RandLA-Net,":[30],"state-of-the-art":[32],"neural":[33],"network":[34],"architecture,":[35],"for":[36,77,138,163],"3D":[38,98,142],"large-scale":[41],"in":[45,141,154,180],"urban":[46,80,117,164,187],"areas.":[47,188],"The":[48,123,146,168],"focuses":[50],"three":[52],"major":[53],"Chinese":[54,186],"cities,":[55],"namely":[56],"Chengdu,":[57],"Jiaoda,":[58],"Shenzhen,":[60],"leveraging":[61],"their":[62],"unique":[63],"characteristics":[64],"to":[65,100,110,114,151,171],"enhance":[66],"performance.":[68],"To":[69],"address":[70],"limited":[72],"availability":[73],"labeled":[75],"these":[78],"specific":[79],"areas,":[81,118],"we":[82,106],"employed":[83],"transfer":[84,147],"learning":[85,148],"techniques.":[86],"We":[87],"transferred":[88],"learned":[90],"weights":[91],"from":[92],"Sensat":[94],"Toronto":[97],"datasets":[99],"initialize":[101],"our":[102],"RandLA-Net":[103],"model.":[104],"Additionally,":[105],"performed":[107],"class":[108],"remapping":[109],"adapt":[111],"model":[113],"target":[116],"ensuring":[119],"results.":[122],"experimental":[124],"results":[125],"demonstrate":[126],"effectiveness":[128],"proposed":[131],"approach":[132],"achieving":[133],"over":[134],"80\\%":[135],"F1":[136],"score":[137],"each":[139],"areas":[140],"segmentation.":[145],"strategy":[149],"proves":[150],"be":[152],"crucial":[153],"overcoming":[155],"scarcity":[157],"issues,":[158],"providing":[159],"robust":[161],"solution":[162],"analysis.":[167],"findings":[169],"contribute":[170],"advancement":[173],"methods,":[178],"especially":[179],"context":[182],"rapidly":[184],"evolving":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-12-22T00:00:00"}