{"id":"https://openalex.org/W3135229275","doi":"https://doi.org/10.1145/3448823.3448842","title":"GDS","display_name":"GDS","publication_year":2020,"publication_date":"2020-12-09","ids":{"openalex":"https://openalex.org/W3135229275","doi":"https://doi.org/10.1145/3448823.3448842","mag":"3135229275"},"language":"en","primary_location":{"id":"doi:10.1145/3448823.3448842","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448823.3448842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing","raw_type":"proceedings-article"},"type":"article","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/A5067551607","display_name":"Jiahua Wang","orcid":"https://orcid.org/0000-0002-5299-6968"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahua Wang","raw_affiliation_strings":["Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362745","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418152","display_name":"Ting Liu","orcid":"https://orcid.org/0000-0002-8468-4926"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Liu","raw_affiliation_strings":["Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006854141","display_name":"Shikui Wei","orcid":"https://orcid.org/0000-0003-3803-9763"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikui Wei","raw_affiliation_strings":["Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science Beijing Jiaotong University, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067551607"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.5282,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62581176,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.995199978351593,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7741784453392029},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.758932888507843},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6918683052062988},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6721463203430176},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5901362299919128},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5149453282356262},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.46413132548332214},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46081843972206116},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4395415484905243},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43590855598449707},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4356752634048462},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4128801226615906},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3906179368495941},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32614296674728394},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.29831886291503906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14858689904212952}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7741784453392029},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758932888507843},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6918683052062988},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6721463203430176},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5901362299919128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5149453282356262},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.46413132548332214},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46081843972206116},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4395415484905243},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43590855598449707},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4356752634048462},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4128801226615906},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3906179368495941},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32614296674728394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29831886291503906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14858689904212952},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448823.3448842","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448823.3448842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2958073455","https://openalex.org/W2962701877","https://openalex.org/W2963094037","https://openalex.org/W2963158438","https://openalex.org/W2963719584","https://openalex.org/W2979750740","https://openalex.org/W2981440248","https://openalex.org/W2981983525","https://openalex.org/W2983098675","https://openalex.org/W2990613095","https://openalex.org/W3034664537","https://openalex.org/W3177525997","https://openalex.org/W4301045096"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"In":[0,57],"deep":[1],"neural":[2],"networks":[3,155],"for":[4,16,129],"3D":[5,130,152],"point":[6,37,77,131],"clouds,":[7],"the":[8,19,45,75,93,108,146,162],"down-":[9],"sampling":[10,38],"operation":[11,127],"is":[12,51],"a":[13,62,116],"key":[14],"module":[15,99,120],"effectively":[17,157],"improving":[18],"computational":[20],"efficiency":[21],"as":[22,24],"well":[23],"boosting":[25],"robustness":[26],"to":[27,39,69,71,92,121],"variation":[28],"of":[29,161],"input":[30,76],"points.":[31],"Previous":[32],"works":[33],"mainly":[34],"utilize":[35],"furthest":[36],"down-sample":[40],"points":[41,73,87,102],"in":[42,79],"accordance":[43,80],"with":[44,81,89,115],"spatial":[46],"distance":[47],"between":[48],"points,":[49],"which":[50],"an":[52],"offline":[53],"and":[54,104,141,149],"time-consuming":[55],"operation.":[56],"this":[58],"paper,":[59],"we":[60],"propose":[61],"Global":[63,123],"Description":[64,124],"guided":[65,125],"down-Sampling":[66],"method":[67],"(GDS)":[68],"learn":[70],"sample":[72],"from":[74],"set":[78],"their":[82,105],"features.":[83],"Specifically,":[84],"through":[85],"retaining":[86],"features":[88,103],"high":[90],"affinity":[91],"global":[94],"shape":[95],"description,":[96],"our":[97,113],"GDS":[98,114,148],"preserve":[100],"significant":[101],"coordinates":[106],"on":[107,135],"fly.":[109],"We":[110],"also":[111],"equip":[112],"locality":[117],"feature":[118],"aggregation":[119],"form":[122],"Pooling":[126],"(GDP)":[128],"networks.":[132],"Experimental":[133],"results":[134],"two":[136],"publicly":[137],"available":[138],"datasets,":[139],"ModelNet":[140],"ScanObjectNN,":[142],"show":[143],"that":[144],"introducing":[145],"proposed":[147],"GDP":[150],"into":[151],"object":[153],"classification":[154],"can":[156],"reduce":[158],"about":[159],"45%":[160],"forward":[163],"propagation":[164],"time":[165],"while":[166],"achieving":[167],"higher":[168],"accuracy.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-03-15T00:00:00"}