{"id":"https://openalex.org/W4401892425","doi":"https://doi.org/10.3390/rs16173127","title":"GSSnowflake: Point Cloud Completion by Snowflake with Grouped Vector and Self-Positioning Point Attention","display_name":"GSSnowflake: Point Cloud Completion by Snowflake with Grouped Vector and Self-Positioning Point Attention","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401892425","doi":"https://doi.org/10.3390/rs16173127"},"language":"en","primary_location":{"id":"doi:10.3390/rs16173127","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173127","pdf_url":"https://www.mdpi.com/2072-4292/16/17/3127/pdf?version=1724506292","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/17/3127/pdf?version=1724506292","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113109866","display_name":"Yu Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Xiao","raw_affiliation_strings":["The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113971807","display_name":"Yi-Sheng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yisheng Chen","raw_affiliation_strings":["The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060050761","display_name":"Chongcheng Chen","orcid":"https://orcid.org/0000-0001-5509-4188"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongcheng Chen","raw_affiliation_strings":["The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100782028","display_name":"Lin Ding","orcid":"https://orcid.org/0000-0002-6815-5557"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ding Lin","raw_affiliation_strings":["The Academy of Digital China, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"The Academy of Digital China, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100782028"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.7907,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67208616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"16","issue":"17","first_page":"3127","last_page":"3127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9973999857902527,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9944999814033508,"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/overfitting","display_name":"Overfitting","score":0.8276803493499756},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8209378719329834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520177364349365},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5594961643218994},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5290559530258179},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4961725175380707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4530075788497925},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3884986340999603},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34208738803863525},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.17127904295921326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15702196955680847}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8276803493499756},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8209378719329834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520177364349365},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5594961643218994},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5290559530258179},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4961725175380707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4530075788497925},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3884986340999603},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34208738803863525},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.17127904295921326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15702196955680847},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs16173127","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173127","pdf_url":"https://www.mdpi.com/2072-4292/16/17/3127/pdf?version=1724506292","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4c80dea03f044c0daf988e4246c14396","is_oa":true,"landing_page_url":"https://doaj.org/article/4c80dea03f044c0daf988e4246c14396","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 17, p 3127 (2024)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/16/17/3127/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs16173127","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs16173127","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16173127","pdf_url":"https://www.mdpi.com/2072-4292/16/17/3127/pdf?version=1724506292","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G8559485828","display_name":null,"funder_award_id":"5211HZ220007","funder_id":"https://openalex.org/F4320336311","funder_display_name":"State Grid Zhejiang Electric Power Company"}],"funders":[{"id":"https://openalex.org/F4320336311","display_name":"State Grid Zhejiang Electric Power Company","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401892425.pdf","grobid_xml":"https://content.openalex.org/works/W4401892425.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2466594406","https://openalex.org/W2559882727","https://openalex.org/W2601564443","https://openalex.org/W2603429625","https://openalex.org/W2624503621","https://openalex.org/W2788158258","https://openalex.org/W2796426482","https://openalex.org/W2798314605","https://openalex.org/W2885285090","https://openalex.org/W2886499109","https://openalex.org/W2950642167","https://openalex.org/W2962928871","https://openalex.org/W2963182550","https://openalex.org/W3034552520","https://openalex.org/W3035014292","https://openalex.org/W3105863736","https://openalex.org/W3109518641","https://openalex.org/W3111535274","https://openalex.org/W3125010829","https://openalex.org/W3153465022","https://openalex.org/W3166470370","https://openalex.org/W3170469318","https://openalex.org/W3170754649","https://openalex.org/W3203898101","https://openalex.org/W3206075451","https://openalex.org/W4214755140","https://openalex.org/W4220890232","https://openalex.org/W4221158735","https://openalex.org/W4306175953","https://openalex.org/W4307339700","https://openalex.org/W4313183789","https://openalex.org/W4379881908","https://openalex.org/W4386072236","https://openalex.org/W4386075508","https://openalex.org/W4393150773","https://openalex.org/W4393154253","https://openalex.org/W6640300118","https://openalex.org/W6739901393","https://openalex.org/W6754997583","https://openalex.org/W6810204697"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Point":[0],"clouds":[1],"are":[2],"essential":[3],"3D":[4],"data":[5],"representations":[6],"utilized":[7],"across":[8],"various":[9],"disciplines,":[10],"often":[11],"requiring":[12],"point":[13,182],"cloud":[14,183],"completion":[15,22,184],"methods":[16,23],"to":[17,39,57,94,148,179],"address":[18,49],"inherent":[19],"incompleteness.":[20],"Existing":[21],"like":[24],"SnowflakeNet":[25],"only":[26],"consider":[27],"local":[28],"attention,":[29],"lacking":[30],"global":[31,61,76],"information":[32],"of":[33,127,133],"the":[34,44,75,88,107,113,139,152,162],"complete":[35,60],"shape,":[36],"and":[37,64,90,100,129,136,143,159,169,172,175],"tend":[38],"suffer":[40],"from":[41],"overfitting":[42],"as":[43,110,112],"model":[45],"depth":[46],"increases.":[47],"To":[48],"these":[50],"issues,":[51],"we":[52,79,150],"introduced":[53],"self-positioning":[54,91],"point-based":[55,92],"attention":[56,83,93],"better":[58],"capture":[59],"contextual":[62],"features":[63],"designed":[65],"a":[66,81],"Channel":[67],"Attention":[68],"module":[69],"for":[70],"adaptive":[71],"feature":[72],"adjustment":[73],"within":[74],"vector.":[77],"Additionally,":[78],"implemented":[80],"vector":[82],"grouping":[84],"strategy":[85],"in":[86],"both":[87],"skip-transformer":[89],"mitigate":[95],"overfitting,":[96],"improving":[97],"parameter":[98],"efficiency":[99],"generalization.":[101],"We":[102],"evaluated":[103],"our":[104,121,186],"method":[105,122,187],"on":[106,138,161],"PCN":[108],"dataset":[109],"well":[111],"ShapeNet55/34":[114],"datasets.":[115],"The":[116],"experimental":[117],"results":[118],"show":[119],"that":[120],"achieved":[123],"an":[124],"average":[125,130,153],"CD-L1":[126],"7.09":[128],"CD-L2":[131],"scores":[132],"8.0,":[134],"7.8,":[135],"14.4":[137],"PCN,":[140],"ShapeNet55,":[141],"ShapeNet34,":[142],"ShapeNet-unseen21":[144],"benchmarks,":[145,164],"respectively.":[146],"Compared":[147,178],"SnowflakeNet,":[149],"improved":[151],"CD":[154],"by":[155],"1.6%,":[156],"3.6%,":[157],"3.7%,":[158],"4.6%":[160],"corresponding":[163],"while":[165],"also":[166,188],"reducing":[167],"complexity":[168],"computational":[170],"costs":[171],"accelerating":[173],"training":[174],"inference":[176],"speeds.":[177],"other":[180],"existing":[181],"networks,":[185],"achieves":[189],"competitive":[190],"results.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}