{"id":"https://openalex.org/W4309307980","doi":"https://doi.org/10.3389/fnbot.2022.1029968","title":"Multi-view SoftPool attention convolutional networks for 3D model classification","display_name":"Multi-view SoftPool attention convolutional networks for 3D model classification","publication_year":2022,"publication_date":"2022-11-16","ids":{"openalex":"https://openalex.org/W4309307980","doi":"https://doi.org/10.3389/fnbot.2022.1029968","pmid":"https://pubmed.ncbi.nlm.nih.gov/36467567"},"language":"en","primary_location":{"id":"doi:10.3389/fnbot.2022.1029968","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2022.1029968","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2022.1029968/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2022.1029968/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001514481","display_name":"Wenju Wang","orcid":"https://orcid.org/0000-0002-8549-4710"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenju Wang","raw_affiliation_strings":["College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395178","display_name":"Xiaolin Wang","orcid":"https://orcid.org/0000-0003-4293-7523"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaolin Wang","raw_affiliation_strings":["College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389271","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-5145-5529"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069159378","display_name":"Haoran Zhou","orcid":"https://orcid.org/0000-0002-3530-0500"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Zhou","raw_affiliation_strings":["College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100395178"],"corresponding_institution_ids":["https://openalex.org/I148128674"],"apc_list":{"value":2950,"currency":"USD","value_usd":2950},"apc_paid":{"value":2950,"currency":"USD","value_usd":2950},"fwci":1.3277,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.76716735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"16","issue":null,"first_page":"1029968","last_page":"1029968"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.7627000212669373,"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":0.7627000212669373,"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":0.050599999725818634,"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/T12290","display_name":"Human Motion and Animation","score":0.023000000044703484,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/computer-science","display_name":"Computer science","score":0.8864234089851379},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6256675124168396},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6083702445030212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5817904472351074},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5691348314285278},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5634405612945557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5097576975822449},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5047999620437622},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.485924631357193},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47894221544265747},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4715801775455475},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34822142124176025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3258487582206726},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2034783959388733},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0659913718700409}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8864234089851379},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6256675124168396},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6083702445030212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5817904472351074},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5691348314285278},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5634405612945557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5097576975822449},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5047999620437622},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.485924631357193},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47894221544265747},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4715801775455475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34822142124176025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3258487582206726},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2034783959388733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0659913718700409},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fnbot.2022.1029968","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2022.1029968","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2022.1029968/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},{"id":"pmid:36467567","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36467567","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in neurorobotics","raw_type":null},{"id":"pmh:oai:doaj.org/article:72ac2611a78a405191ffa25263f48ba9","is_oa":true,"landing_page_url":"https://doaj.org/article/72ac2611a78a405191ffa25263f48ba9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Neurorobotics, Vol 16 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9709409","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9709409","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Front Neurorobot","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/fnbot.2022.1029968","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2022.1029968","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2022.1029968/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[{"id":"https://openalex.org/G6766094321","display_name":null,"funder_award_id":"19ZR1435900","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309307980.pdf","grobid_xml":"https://content.openalex.org/works/W4309307980.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1973644502","https://openalex.org/W2113030220","https://openalex.org/W2194775991","https://openalex.org/W2211722331","https://openalex.org/W2556802233","https://openalex.org/W2738620947","https://openalex.org/W2798777114","https://openalex.org/W2798998662","https://openalex.org/W2799162093","https://openalex.org/W2800466466","https://openalex.org/W2890018557","https://openalex.org/W2896196878","https://openalex.org/W2903414915","https://openalex.org/W2921891839","https://openalex.org/W2952074843","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2964161804","https://openalex.org/W2964342398","https://openalex.org/W2968474279","https://openalex.org/W2979750740","https://openalex.org/W2981440248","https://openalex.org/W2986519121","https://openalex.org/W3008103485","https://openalex.org/W3011148091","https://openalex.org/W3012015905","https://openalex.org/W3012494314","https://openalex.org/W3018874968","https://openalex.org/W3025802147","https://openalex.org/W3026237693","https://openalex.org/W3035541121","https://openalex.org/W3042388945","https://openalex.org/W3083861253","https://openalex.org/W3089947940","https://openalex.org/W3090285615","https://openalex.org/W3091184187","https://openalex.org/W3107191128","https://openalex.org/W3107379492","https://openalex.org/W3126181914","https://openalex.org/W3211094034","https://openalex.org/W4302429281","https://openalex.org/W6640300118","https://openalex.org/W6739778489","https://openalex.org/W6752378368","https://openalex.org/W6758748852","https://openalex.org/W6763422710","https://openalex.org/W6775845032","https://openalex.org/W6777394587","https://openalex.org/W6788307039","https://openalex.org/W6796931752"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W2953234277","https://openalex.org/W2748922771"],"abstract_inverted_index":{"Introduction:":[0],"Existing":[1],"multi-view-based":[2],"3D":[3,47,70,135,144],"model":[4,48,145,181],"classification":[5,32,49,146,185],"methods":[6],"have":[7],"the":[8,21,31,64,73,76,86,89,94,101,110,114,122,125,183],"problems":[9],"of":[10,20,75,124,176],"insufficient":[11],"view":[12],"refinement":[13,96],"feature":[14,78],"extraction":[15,79],"and":[16,59,63,107,158,163,166],"poor":[17],"generalization":[18,123],"ability":[19],"network":[22,45,126],"model,":[23],"which":[24,92,119],"makes":[25],"it":[26],"difficult":[27],"to":[28],"further":[29],"improve":[30],"accuracy.":[33,186],"To":[34],"this":[35,37],"end,":[36],"paper":[38],"proposes":[39],"a":[40,133,142,174],"multi-view":[41,55,77],"SoftPool":[42,82],"attention":[43,102],"convolutional":[44],"for":[46,88],"tasks.":[50],"Methods:":[51],"This":[52],"method":[53,154],"extracts":[54],"features":[56,66],"through":[57],"ResNest":[58],"adaptive":[60],"pooling":[61],"modules,":[62],"extracted":[65],"can":[67],"better":[68],"represent":[69],"models.":[71],"Then,":[72],"results":[74,150],"processed":[80],"using":[81],"are":[83],"used":[84],"as":[85],"Query":[87,106],"self-attentive":[90],"calculation,":[91],"enables":[93],"subsequent":[95],"extraction.":[97],"We":[98],"then":[99],"input":[100],"scores":[103],"calculated":[104],"by":[105],"Key":[108],"in":[109],"self-attention":[111],"calculation":[112],"into":[113],"mobile":[115],"inverted":[116],"bottleneck":[117],"convolution,":[118],"effectively":[120],"improves":[121],"model.":[127],"Based":[128],"on":[129,161,169],"our":[130,153,179],"proposed":[131],"method,":[132],"compact":[134],"global":[136],"descriptor":[137],"is":[138],"finally":[139],"generated,":[140],"achieving":[141],"high-accuracy":[143],"performance.":[147],"Results:":[148],"Experimental":[149],"showed":[151],"that":[152],"achieves":[155,182],"96.96%":[156],"OA":[157,165],"95.68%":[159],"AA":[160,168],"ModelNet40":[162],"98.57%":[164],"98.42%":[167],"ModelNet10.":[170],"Discussion:":[171],"Compared":[172],"with":[173],"multitude":[175],"popular":[177],"methods,":[178],"algorithm":[180],"state-of-the-art":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
