{"id":"https://openalex.org/W3199971500","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533464","title":"CM-Net: a point cloud upsampling network based on adversarial neural network","display_name":"CM-Net: a point cloud upsampling network based on adversarial neural network","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199971500","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533464","mag":"3199971500"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5100427643","display_name":"Xiaomeng Li","orcid":"https://orcid.org/0000-0003-1105-8083"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaomeng Li","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090106064","display_name":"Chung\u2010Ming Own","orcid":"https://orcid.org/0000-0002-2106-7226"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chung-Ming Own","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018836811","display_name":"Kaizhen Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaizhen Wu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103218833","display_name":"Qian Sun","orcid":"https://orcid.org/0000-0002-2098-9878"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Sun","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100427643"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.5254,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60799955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.998199999332428,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8773472309112549},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8356595039367676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7107865214347839},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6733953356742859},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5174849033355713},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.44992080330848694},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44317370653152466},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.426643967628479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3713345527648926},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3671761155128479},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17960697412490845},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.1394447386264801},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13228559494018555},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10487878322601318},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07628831267356873}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8773472309112549},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8356595039367676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7107865214347839},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6733953356742859},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5174849033355713},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.44992080330848694},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44317370653152466},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.426643967628479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3713345527648926},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3671761155128479},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17960697412490845},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.1394447386264801},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13228559494018555},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10487878322601318},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07628831267356873},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6899999976158142,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1988317275","https://openalex.org/W2025973801","https://openalex.org/W2081194966","https://openalex.org/W2137531922","https://openalex.org/W2169611956","https://openalex.org/W2194775991","https://openalex.org/W2560609797","https://openalex.org/W2738588019","https://openalex.org/W2962701877","https://openalex.org/W2963121255","https://openalex.org/W2963390820","https://openalex.org/W2963680153","https://openalex.org/W2997337685"],"related_works":["https://openalex.org/W3214732802","https://openalex.org/W3209202081","https://openalex.org/W4226324275","https://openalex.org/W2953246223","https://openalex.org/W4293320219","https://openalex.org/W3110074278","https://openalex.org/W4283584549","https://openalex.org/W2618858825","https://openalex.org/W2554314924","https://openalex.org/W2998859928"],"abstract_inverted_index":{"In":[0],"the":[1,5,17,23,29,84,108,110,125,136,146],"real-life":[2],"application":[3,18],"scenarios,":[4],"collected":[6],"point":[7,34,41,45,49,58,87,93,137],"clouds":[8,42,46],"are":[9],"often":[10],"sparse,":[11],"noisy":[12],"and":[13,75,103,118,144],"non-uniform,":[14],"especially":[15],"if":[16],"is":[19,81],"unable":[20],"to":[21,28,38,82],"capture":[22],"local":[24],"spatial":[25],"layout":[26],"due":[27],"lack":[30],"of":[31,70],"points.":[32,149],"Thus,":[33],"cloud":[35,59,88,94],"upsampling":[36,60,92],"aims":[37],"transform":[39],"sparse":[40,86],"into":[43,89],"dense":[44,91],"with":[47,95],"uniform":[48],"distribution.":[50],"This":[51],"study":[52],"proposes":[53],"a":[54,73,76,90,115,119],"generative":[55],"adversarial":[56],"network-based":[57],"network":[61,121,133],"called":[62],"CM-Net":[63],"(Circular":[64],"Multi-Frequency":[65],"Network).":[66],"The":[67,78],"model":[68],"consists":[69],"two":[71,113],"parts:":[72],"generator":[74],"discriminator.":[77],"generator's":[79,126],"purpose":[80],"convert":[83],"input":[85],"our":[96,132],"specific":[97],"parts,":[98],"includes":[99],"multi-frequency":[100],"pooling":[101],"module":[102],"positive":[104],"polygon-based":[105],"code.":[106],"On":[107],"contrary,":[109],"discriminator":[111],"incudes":[112],"parts;":[114],"feature":[116],"extractor":[117],"convolutional":[120],"module,":[122],"which":[123],"optimizes":[124],"performance.":[127],"Experimental":[128],"results":[129],"show":[130],"that":[131],"can":[134],"learn":[135],"cloud's":[138],"underlying":[139],"geometric":[140],"information":[141],"very":[142],"well,":[143],"complete":[145],"even":[147],"distribution":[148]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}