{"id":"https://openalex.org/W4285410152","doi":"https://doi.org/10.1145/3532213.3532321","title":"PU-LNGCN: Multi-scale Design of Point Cloud Upsampling Using Graph Convolutional Networks","display_name":"PU-LNGCN: Multi-scale Design of Point Cloud Upsampling Using Graph Convolutional Networks","publication_year":2022,"publication_date":"2022-03-18","ids":{"openalex":"https://openalex.org/W4285410152","doi":"https://doi.org/10.1145/3532213.3532321"},"language":"en","primary_location":{"id":"doi:10.1145/3532213.3532321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532213.3532321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101536111","display_name":"Haoran Ma","orcid":"https://orcid.org/0000-0003-1567-713X"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Ma","raw_affiliation_strings":["School of Software, Tiangong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Tiangong University, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048371289","display_name":"Jianming Wang","orcid":"https://orcid.org/0000-0003-2685-4437"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Wang","raw_affiliation_strings":["School of Computer Science and Technology, Tiangong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020541310","display_name":"Yukuan Sun","orcid":"https://orcid.org/0000-0002-8886-6137"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yukuan Sun","raw_affiliation_strings":["Center for Engineering Intership and Training, Tiangong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Engineering Intership and Training, Tiangong University, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061867895","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-5339-5427"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["School of Life Science, Tiangong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Life Science, Tiangong University, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I198091727"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13178936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"711","last_page":"718"},"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":0.9993000030517578,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8511768579483032},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8064179420471191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7754068970680237},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.635036826133728},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5455098748207092},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5152747631072998},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4829670488834381},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.46943119168281555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40091291069984436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3649066388607025},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29749348759651184},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09510597586631775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07525339722633362}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8511768579483032},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8064179420471191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754068970680237},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.635036826133728},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5455098748207092},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5152747631072998},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4829670488834381},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.46943119168281555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40091291069984436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3649066388607025},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29749348759651184},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09510597586631775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07525339722633362},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3532213.3532321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532213.3532321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1794881434","display_name":null,"funder_award_id":"62072335; 61872269;61903273","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1885185971","https://openalex.org/W2166681504","https://openalex.org/W2183341477","https://openalex.org/W2242218935","https://openalex.org/W2928165649","https://openalex.org/W2962928871","https://openalex.org/W2963372104","https://openalex.org/W2963390820","https://openalex.org/W2963470893","https://openalex.org/W2963680153","https://openalex.org/W2979750740","https://openalex.org/W2990045899","https://openalex.org/W2997337685","https://openalex.org/W3145013517","https://openalex.org/W3184736166"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4385574037","https://openalex.org/W3176213335","https://openalex.org/W4212888438"],"abstract_inverted_index":{"Learning":[0],"and":[1,16,29,35,75,129,140,150,170],"analyzing":[2],"3D":[3],"point":[4,31,38,92,116,126,153],"clouds":[5,32,154],"with":[6],"deep":[7],"neural":[8],"networks":[9],"is":[10],"challenging":[11],"due":[12],"to":[13,63,87],"the":[14,20,24,72,113,120],"irregular":[15],"unordered":[17,30],"nature":[18],"of":[19,26,68,91],"data.":[21],"Therefore,":[22],"as":[23,155,157],"task":[25],"converting":[27],"sparse":[28],"into":[33,124],"dense":[34],"complete":[36],"ones,":[37],"cloud":[39,93],"upsampling":[40,127],"has":[41],"attracted":[42],"extensive":[43,138],"attention.":[44],"In":[45],"this":[46,105],"paper,":[47],"we":[48,143],"specially":[49],"design":[50],"a":[51,78,131],"structure-based":[52],"graph":[53],"convolutional":[54],"network":[55],"called":[56,84,134],"Local":[57],"Neighborhood":[58],"Graph":[59],"Convolutional":[60],"Network":[61],"(LNGCN)":[62],"fully":[64],"exploit":[65],"structural":[66],"information":[67,90],"graph.":[69],"We":[70,118],"introduce":[71],"proposed":[73],"LNGCN":[74,86,122],"further":[76,109],"propose":[77,130],"novel":[79],"multi-scale":[80],"feature":[81,106],"extraction":[82],"block":[83,123],"Multiscale":[85,121],"encode":[88],"rich":[89],"data":[94,160],"at":[95,102],"different":[96],"granular":[97],"levels.":[98],"By":[99,136],"aggregating":[100],"features":[101],"multiple":[103],"scales,":[104],"extractor":[107],"enables":[108],"performance":[110],"improvement":[111],"in":[112],"final":[114],"upsampled":[115],"clouds.":[117],"combine":[119],"current":[125],"pipelines":[128],"new":[132],"architecture":[133],"PU-LNGCN.":[135],"using":[137],"quantitative":[139],"qualitative":[141],"experiments,":[142],"show":[144],"that":[145],"PU-LNGCN":[146,166],"can":[147],"handle":[148],"noisy":[149],"non-uniformly":[151],"distributed":[152],"well":[156],"real":[158],"scanned":[159],"by":[161],"LiDAR":[162],"sensors":[163],"very":[164],"well.":[165],"outperforms":[167],"previous":[168],"methods":[169],"achieves":[171],"state-of-the-art":[172],"performance.":[173]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
