{"id":"https://openalex.org/W4403059129","doi":"https://doi.org/10.1109/access.2024.3472301","title":"3D Directional Encoding for Point Cloud Analysis","display_name":"3D Directional Encoding for Point Cloud Analysis","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403059129","doi":"https://doi.org/10.1109/access.2024.3472301"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3472301","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3472301","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3472301","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102581559","display_name":"Yoonjae Jung","orcid":"https://orcid.org/0009-0002-0963-2381"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yoonjae Jung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0009-0002-0963-2381","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444575","display_name":"Sang-Hyun Lee","orcid":"https://orcid.org/0009-0007-3360-4758"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Hyun Lee","raw_affiliation_strings":["Department of AI Mobility Engineering, Ajou University, Suwon, South Korea"],"raw_orcid":"https://orcid.org/0009-0007-3360-4758","affiliations":[{"raw_affiliation_string":"Department of AI Mobility Engineering, Ajou University, Suwon, South Korea","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048311228","display_name":"Seung\u2010Woo Seo","orcid":"https://orcid.org/0000-0003-4890-8563"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung-Woo Seo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4890-8563","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19665742,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"144533","last_page":"144543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9950000047683716,"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"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9950000047683716,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9948999881744385,"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":0.9911999702453613,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6034679412841797},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5600205063819885},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.46807989478111267},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4281131625175476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15702050924301147},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10690182447433472},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0907820463180542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6034679412841797},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5600205063819885},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.46807989478111267},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4281131625175476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15702050924301147},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10690182447433472},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0907820463180542},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3472301","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3472301","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ad30d4acc1cb4ba8a5663a5e60b95514","is_oa":true,"landing_page_url":"https://doaj.org/article/ad30d4acc1cb4ba8a5663a5e60b95514","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":"IEEE Access, Vol 12, Pp 144533-144543 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3472301","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3472301","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6499999761581421,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1901129140","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2460657278","https://openalex.org/W2553307952","https://openalex.org/W2560609797","https://openalex.org/W2963231572","https://openalex.org/W2963727135","https://openalex.org/W2979750740","https://openalex.org/W2981440248","https://openalex.org/W2990613095","https://openalex.org/W3034314779","https://openalex.org/W3035398346","https://openalex.org/W3201923677","https://openalex.org/W3204568647","https://openalex.org/W4214755140","https://openalex.org/W4385245566","https://openalex.org/W4386065814","https://openalex.org/W4386066101","https://openalex.org/W4386076422","https://openalex.org/W4387129532","https://openalex.org/W6739778489","https://openalex.org/W6757817989","https://openalex.org/W6765299845","https://openalex.org/W6790453339","https://openalex.org/W6802749810","https://openalex.org/W6810249204","https://openalex.org/W6810976116","https://openalex.org/W6839446344","https://openalex.org/W6846166657","https://openalex.org/W6856539668"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W1997222214"],"abstract_inverted_index":{"Extracting":[0],"informative":[1],"local":[2,33,54,126,149],"features":[3,102,151,174],"in":[4,161,186],"point":[5,16,101,134,150,176,218],"clouds":[6],"is":[7,113,182],"crucial":[8],"for":[9,109],"accurately":[10],"understanding":[11],"spatial":[12,51,91,99,110,170],"information":[13],"inside":[14],"3D":[15,82],"data.":[17],"Previous":[18],"works":[19],"utilize":[20],"either":[21],"complex":[22,36],"network":[23],"designs":[24],"or":[25],"simple":[26,44],"multi-layer":[27],"perceptrons":[28],"(MLP)":[29],"to":[30,48,62],"extract":[31,133],"the":[32,50,119,209],"features.":[34],"However,":[35],"networks":[37],"often":[38],"incur":[39],"high":[40],"computational":[41,95],"cost,":[42],"whereas":[43],"MLP":[45],"may":[46],"struggle":[47],"capture":[49],"relations":[52,92],"among":[53],"points":[55,127],"effectively.":[56],"These":[57],"challenges":[58],"limit":[59],"their":[60],"scalability":[61],"delicate":[63],"and":[64,71,100,128,159,171,184,188,200],"real-time":[65],"tasks,":[66],"such":[67],"as":[68],"autonomous":[69],"driving":[70],"robot":[72],"navigation.":[73],"To":[74,132],"address":[75],"these":[76],"challenges,":[77],"we":[78,136],"propose":[79,138],"a":[80,162,201],"novel":[81],"Directional":[83,114],"Encoding":[84,115],"Network":[85],"(3D-DENet)":[86],"capable":[87],"of":[88,107,125,148,198,204],"effectively":[89],"encoding":[90],"with":[93],"low":[94],"cost.":[96],"3D-DENet":[97,108,165,181,193],"extracts":[98],"separately.":[103],"The":[104],"key":[105],"component":[106],"feature":[111],"extraction":[112],"(DE),":[116],"which":[117,144],"encodes":[118],"cosine":[120],"similarity":[121],"between":[122],"direction":[123,130],"vectors":[124],"trainable":[129],"vectors.":[131],"features,":[135],"also":[137],"Local":[139],"Point":[140],"Feature":[141],"Multi-Aggregation":[142],"(LPFMA),":[143],"integrates":[145],"various":[146],"aspects":[147],"using":[152,214],"diverse":[153],"aggregation":[154],"functions.":[155],"By":[156],"leveraging":[157],"DE":[158],"LPFMA":[160],"hierarchical":[163],"structure,":[164],"efficiently":[166],"captures":[167],"both":[168],"detailed":[169],"high-level":[172],"semantic":[173],"from":[175],"clouds.":[177],"Experiments":[178],"show":[179],"that":[180],"effective":[183],"efficient":[185],"classification":[187],"segmentation":[189],"tasks.":[190],"In":[191],"particular,":[192],"achieves":[194],"an":[195],"overall":[196],"accuracy":[197,203],"90.7%":[199],"mean":[202],"90.1%":[205],"on":[206],"ScanObjectNN,":[207],"outperforming":[208],"current":[210],"state-of-the-art":[211],"method":[212],"while":[213],"only":[215],"47%":[216],"floating":[217],"operations.":[219]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
