{"id":"https://openalex.org/W2998083489","doi":"https://doi.org/10.1109/tits.2019.2961060","title":"Multi-Scale Point-Wise Convolutional Neural Networks for 3D Object Segmentation From LiDAR Point Clouds in Large-Scale Environments","display_name":"Multi-Scale Point-Wise Convolutional Neural Networks for 3D Object Segmentation From LiDAR Point Clouds in Large-Scale Environments","publication_year":2019,"publication_date":"2019-12-27","ids":{"openalex":"https://openalex.org/W2998083489","doi":"https://doi.org/10.1109/tits.2019.2961060","mag":"2998083489"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2961060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2961060","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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":"https://openalex.org/A5032270954","display_name":"Lingfei Ma","orcid":"https://orcid.org/0000-0001-8893-9693"},"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":"Lingfei Ma","raw_affiliation_strings":["Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0001-8893-9693","affiliations":[{"raw_affiliation_string":"Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414383","display_name":"Ying Li","orcid":"https://orcid.org/0000-0003-0608-9619"},"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":"Ying Li","raw_affiliation_strings":["Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0608-9619","affiliations":[{"raw_affiliation_string":"Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613889","display_name":"Jonathan Li","orcid":"https://orcid.org/0000-0001-7899-0049"},"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"]},{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Jonathan Li","raw_affiliation_strings":["Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada","Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0001-7899-0049","affiliations":[{"raw_affiliation_string":"Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073137946","display_name":"Weikai Tan","orcid":"https://orcid.org/0000-0001-7133-0419"},"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":"Weikai Tan","raw_affiliation_strings":["Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065937604","display_name":"Yongtao Yu","orcid":"https://orcid.org/0000-0001-7204-9346"},"institutions":[{"id":"https://openalex.org/I4210153869","display_name":"Huaiyin Institute of Technology","ror":"https://ror.org/0555ezg60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153869"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongtao Yu","raw_affiliation_strings":["Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, China"],"raw_orcid":"https://orcid.org/0000-0001-7204-9346","affiliations":[{"raw_affiliation_string":"Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, China","institution_ids":["https://openalex.org/I4210153869"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076765712","display_name":"Michael A. Chapman","orcid":"https://orcid.org/0000-0001-8342-0606"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Michael A. Chapman","raw_affiliation_strings":["Department of Civil Engineering, Ryerson University, Toronto, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Ryerson University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.9573,"has_fulltext":false,"cited_by_count":135,"citation_normalized_percentile":{"value":0.95881328,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"2","first_page":"821","last_page":"836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9980999827384949,"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":0.9969000220298767,"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/point-cloud","display_name":"Point cloud","score":0.8248298168182373},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7298226356506348},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7274616360664368},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.6752951145172119},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6433756947517395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6136035919189453},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6099485158920288},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4753044545650482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46180954575538635},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4251975417137146},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4186170697212219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3761194944381714}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8248298168182373},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7298226356506348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7274616360664368},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6752951145172119},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6433756947517395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6136035919189453},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6099485158920288},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4753044545650482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46180954575538635},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4251975417137146},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4186170697212219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3761194944381714},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2961060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2961060","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1205905451","display_name":null,"funder_award_id":"RGPIN-50503-10284","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G1552547945","display_name":"\u57fa\u4e8e\u4e09\u7ef4\u70b9\u4e91\u7684\u9ad8\u6e05\u5730\u56fe\u5feb\u901f\u8bed\u4e49\u6807\u6ce8\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41871380","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"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W1482825550","https://openalex.org/W1564871316","https://openalex.org/W1644641054","https://openalex.org/W1781857629","https://openalex.org/W1905882502","https://openalex.org/W1920022804","https://openalex.org/W1972485825","https://openalex.org/W1986473362","https://openalex.org/W2004030129","https://openalex.org/W2057960707","https://openalex.org/W2075597533","https://openalex.org/W2076063813","https://openalex.org/W2099606917","https://openalex.org/W2100657858","https://openalex.org/W2130558599","https://openalex.org/W2160643963","https://openalex.org/W2160821342","https://openalex.org/W2163605009","https://openalex.org/W2211722331","https://openalex.org/W2295332248","https://openalex.org/W2342223463","https://openalex.org/W2344371161","https://openalex.org/W2344796101","https://openalex.org/W2412782625","https://openalex.org/W2555618208","https://openalex.org/W2556802233","https://openalex.org/W2560609797","https://openalex.org/W2586114507","https://openalex.org/W2594519801","https://openalex.org/W2603429625","https://openalex.org/W2606202972","https://openalex.org/W2750632489","https://openalex.org/W2756945571","https://openalex.org/W2764034829","https://openalex.org/W2769312834","https://openalex.org/W2770046775","https://openalex.org/W2782522152","https://openalex.org/W2788158258","https://openalex.org/W2796288287","https://openalex.org/W2800846474","https://openalex.org/W2804872164","https://openalex.org/W2810641456","https://openalex.org/W2849000462","https://openalex.org/W2883597661","https://openalex.org/W2893333163","https://openalex.org/W2902218628","https://openalex.org/W2902302021","https://openalex.org/W2913972737","https://openalex.org/W2914608630","https://openalex.org/W2919534447","https://openalex.org/W2919688329","https://openalex.org/W2922326277","https://openalex.org/W2934180171","https://openalex.org/W2949708697","https://openalex.org/W2962731536","https://openalex.org/W2962759414","https://openalex.org/W2962928871","https://openalex.org/W2963046128","https://openalex.org/W2963121255","https://openalex.org/W2963150697","https://openalex.org/W2963158438","https://openalex.org/W2963226018","https://openalex.org/W2963231572","https://openalex.org/W2964257316","https://openalex.org/W2979750740","https://openalex.org/W3004237909","https://openalex.org/W3101921002","https://openalex.org/W3103830808","https://openalex.org/W6640300118","https://openalex.org/W6683253545","https://openalex.org/W6684191040","https://openalex.org/W6733367512","https://openalex.org/W6739778489","https://openalex.org/W6747904511","https://openalex.org/W6750353395","https://openalex.org/W6753266022","https://openalex.org/W6756639113","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4205800335","https://openalex.org/W2055202857","https://openalex.org/W2022929107","https://openalex.org/W80586315","https://openalex.org/W2758994127"],"abstract_inverted_index":{"Although":[0],"significant":[1],"improvement":[2],"has":[3],"been":[4],"achieved":[5],"in":[6,37,48,71,136,139,143,150,173,202,227],"fully":[7],"autonomous":[8],"driving":[9],"and":[10,29,39,100,133,186,205,232],"semantic":[11,224],"high-definition":[12],"map":[13],"(HD)":[14],"domains,":[15],"most":[16],"of":[17],"the":[18,167],"existing":[19,76],"3D":[20,43,61,118,151],"point":[21,44,62,77,152,199,215],"cloud":[22,45,63,78,200,216],"segmentation":[23,64,79,187,225,230],"methods":[24,80],"cannot":[25],"provide":[26],"high":[27],"representativeness":[28],"remarkable":[30],"robustness.":[31,234],"The":[32,190,208],"principally":[33],"increasing":[34],"challenges":[35],"remain":[36],"completely":[38],"efficiently":[40],"extracting":[41],"high-level":[42,146],"features,":[46],"specifically":[47],"large-scale":[49,197],"road":[50],"environments.":[51,207],"This":[52,103],"paper":[53],"provides":[54],"an":[55,159],"end-to-end":[56],"feature":[57,228],"extraction":[58],"framework":[59,104],"for":[60,184],"by":[65,157,212],"using":[66,158,213],"dynamic":[67],"point-wise":[68,119],"convolutional":[69,87,120,162],"operations":[70],"multiple":[72,137],"scales.":[73],"Compared":[74],"to":[75,97,114,129],"that":[81],"are":[82,154],"commonly":[83],"based":[84,165],"on":[85,166,195],"traditional":[86],"neural":[88,163],"networks":[89],"(CNNs),":[90],"our":[91,219],"proposed":[92,128,191],"method":[93,192,220],"is":[94,111,127,182],"less":[95],"sensitive":[96],"data":[98],"distribution":[99],"computational":[101],"powers.":[102],"mainly":[105],"includes":[106],"four":[107],"modules.":[108],"Module":[109,140,144,174],"I":[110],"first":[112],"designed":[113],"construct":[115],"a":[116,123,176],"revised":[117],"operation.":[121],"Then,":[122],"U-shaped":[124],"downsampling-upsampling":[125],"architecture":[126],"leverage":[130],"both":[131,203],"global":[132],"local":[134,147],"features":[135,149],"scales":[138],"II.":[141],"Next,":[142],"III,":[145],"edge":[148],"neighborhoods":[153],"further":[155],"extracted":[156],"adaptive":[160],"graph":[161],"network":[164],"K-Nearest":[168],"Neighbor":[169],"(KNN)":[170],"algorithm.":[171],"Finally,":[172],"IV,":[175],"conditional":[177],"random":[178],"field":[179],"(CRF)":[180],"algorithm":[181],"developed":[183],"postprocessing":[185],"result":[188],"refinement.":[189],"was":[193],"evaluated":[194],"three":[196],"LiDAR":[198],"datasets":[201],"urban":[204],"indoor":[206],"experimental":[209],"results":[210],"acquired":[211],"different":[214],"scenarios":[217],"indicate":[218],"can":[221],"achieve":[222],"state-of-the-art":[223],"performance":[226],"representativeness,":[229],"accuracy,":[231],"technical":[233]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":5}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
