{"id":"https://openalex.org/W4402365136","doi":"https://doi.org/10.14428/esann/2024.es2024-145","title":"Generalizing Convolution to Point Clouds","display_name":"Generalizing Convolution to Point Clouds","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402365136","doi":"https://doi.org/10.14428/esann/2024.es2024-145"},"language":"en","primary_location":{"id":"doi:10.14428/esann/2024.es2024-145","doi":"https://doi.org/10.14428/esann/2024.es2024-145","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2024.es2024-145","pdf_url":"https://doi.org/10.14428/esann/2024.es2024-145","source":{"id":"https://openalex.org/S7407087818","display_name":"European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2024 proceesdings","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.14428/esann/2024.es2024-145","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053890378","display_name":"Davide Bacciu","orcid":"https://orcid.org/0000-0001-5213-2468","observed_orcids":["https://orcid.org/0000-0001-5213-2468"]},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Bacciu","raw_affiliation_strings":["Universit\u00e0 di Pisa - Department of Computer Science Largo Bruno Pontecorvo , 3 , 56127 , Pisa - Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e0 di Pisa - Department of Computer Science Largo Bruno Pontecorvo , 3 , 56127 , Pisa - Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":null,"display_name":"Francesco Landolfi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Landolfi","raw_affiliation_strings":["Universit\u00e0 di Pisa - Department of Computer Science Largo Bruno Pontecorvo , 3 , 56127 , Pisa - Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e0 di Pisa - Department of Computer Science Largo Bruno Pontecorvo , 3 , 56127 , Pisa - Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I108290504"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"23","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9980000257492065,"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":0.9980000257492065,"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":0.0010000000474974513,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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-clouds","display_name":"point clouds","score":0.6240000128746033},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.9279999732971191},{"id":"https://openalex.org/keywords/point-cloud-classification","display_name":"point cloud classification","score":0.8679999709129333}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7234954833984375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5510106086730957},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5064252614974976},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4907459020614624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.293328195810318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2255387306213379},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1601356565952301},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14428/esann/2024.es2024-145","doi":"https://doi.org/10.14428/esann/2024.es2024-145","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2024.es2024-145","pdf_url":"https://doi.org/10.14428/esann/2024.es2024-145","source":{"id":"https://openalex.org/S7407087818","display_name":"European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2024 proceesdings","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.14428/esann/2024.es2024-145","doi":"https://doi.org/10.14428/esann/2024.es2024-145","is_oa":true,"landing_page_url":"http://doi.org/10.14428/esann/2024.es2024-145","pdf_url":"https://doi.org/10.14428/esann/2024.es2024-145","source":{"id":"https://openalex.org/S7407087818","display_name":"European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2024 proceesdings","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402365136.pdf","grobid_xml":"https://content.openalex.org/works/W4402365136.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3034042948","https://openalex.org/W3029949331","https://openalex.org/W2794561444","https://openalex.org/W2900731076","https://openalex.org/W2935125481","https://openalex.org/W2970800437","https://openalex.org/W3171433839","https://openalex.org/W2938428612","https://openalex.org/W4300559804","https://openalex.org/W3122633743"],"abstract_inverted_index":{"Convolution,":[0],"a":[1,40,84],"fundamental":[2],"operation":[3],"in":[4,28,66],"deep":[5],"learning":[6],"for":[7],"structured":[8],"grid":[9],"data":[10],"like":[11],"images,":[12],"cannot":[13],"be":[14],"directly":[15],"applied":[16],"to":[17,21,49,113],"point":[18,34,57,107],"clouds":[19,35],"due":[20],"their":[22],"irregular":[23],"and":[24],"unordered":[25],"nature.Many":[26],"approaches":[27],"literature":[29],"that":[30,60,87],"perform":[31],"convolution":[32,65],"on":[33,53,104],"achieve":[36],"this":[37],"by":[38,75],"designing":[39],"convolutional":[41],"operator":[42],"from":[43,63],"scratch,":[44],"often":[45],"with":[46,71,83],"little":[47],"resemblance":[48],"the":[50,64,77,80,89,93,98,101,116],"one":[51],"used":[52],"images.We":[54,72],"present":[55],"two":[56,105],"cloud":[58,108],"convolutions":[59],"naturally":[61],"follow":[62],"its":[67],"standard":[68],"definition":[69],"popular":[70],"do":[73],"so":[74],"relaxing":[76],"indexing":[78],"of":[79,92,100],"kernel":[81],"weights":[82],"\"soft\"":[85],"dictionary":[86],"resembles":[88],"attention":[90],"mechanism":[91],"transformers.Finally,":[94],"experimental":[95],"results":[96],"demonstrate":[97],"effectiveness":[99],"proposed":[102],"relaxations":[103],"benchmark":[106],"classification":[109],"tasks.":[110],"Generalizing":[111],"Convolution":[112],"Point":[114],"CloudsGiven":[115],"tensors":[117]},"counts_by_year":[],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2024-09-10T00:00:00"}