{"id":"https://openalex.org/W4389162753","doi":"https://doi.org/10.1109/iccad57390.2023.10323705","title":"Efficient Sampling and Grouping Acceleration for Point Cloud Deep Learning via Single Coordinate Comparison","display_name":"Efficient Sampling and Grouping Acceleration for Point Cloud Deep Learning via Single Coordinate Comparison","publication_year":2023,"publication_date":"2023-10-28","ids":{"openalex":"https://openalex.org/W4389162753","doi":"https://doi.org/10.1109/iccad57390.2023.10323705"},"language":"en","primary_location":{"id":"doi:10.1109/iccad57390.2023.10323705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad57390.2023.10323705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)","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/A5102585590","display_name":"Hyunsung Yoon","orcid":"https://orcid.org/0000-0003-2451-6370"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunsung Yoon","raw_affiliation_strings":["Pohang University of Science and Technology,Pohang,Republic of Korea","Pohang University of Science and Technology, Pohang, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Pohang,Republic of Korea","institution_ids":["https://openalex.org/I123900574"]},{"raw_affiliation_string":"Pohang University of Science and Technology, Pohang, Republic of Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003219699","display_name":"Jae\u2010Joon Kim","orcid":"https://orcid.org/0000-0001-5175-8258"},"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":"Jae-Joon Kim","raw_affiliation_strings":["Seoul National University,Seoul,Republic of Korea","Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102585590"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":0.653,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64620075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9987999796867371,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8599038124084473},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7549566030502319},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6947835683822632},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6574338674545288},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.6180136799812317},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5788195133209229},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5661023855209351},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49244412779808044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4719651937484741},{"id":"https://openalex.org/keywords/distance-transform","display_name":"Distance transform","score":0.45122331380844116},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43061119318008423},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38334548473358154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17533209919929504},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.15878665447235107},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14257419109344482}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8599038124084473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7549566030502319},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6947835683822632},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6574338674545288},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.6180136799812317},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5788195133209229},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5661023855209351},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49244412779808044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4719651937484741},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.45122331380844116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43061119318008423},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38334548473358154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17533209919929504},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.15878665447235107},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14257419109344482},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad57390.2023.10323705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad57390.2023.10323705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1920022804","https://openalex.org/W2211722331","https://openalex.org/W2460657278","https://openalex.org/W2963121255","https://openalex.org/W3034664537","https://openalex.org/W3206429150","https://openalex.org/W3207145355","https://openalex.org/W4214755140","https://openalex.org/W4236965008","https://openalex.org/W4281732104","https://openalex.org/W4313145913","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6839446344"],"related_works":["https://openalex.org/W2389652943","https://openalex.org/W2151165286","https://openalex.org/W2355645862","https://openalex.org/W310595686","https://openalex.org/W785440275","https://openalex.org/W2128178760","https://openalex.org/W2028953289","https://openalex.org/W2052681445","https://openalex.org/W2589110124","https://openalex.org/W2088797232"],"abstract_inverted_index":{"With":[0],"the":[1,7,44,57,70,86,102,115,143,157],"focus":[2],"on":[3,101],"three-dimensional":[4],"(3D)":[5],"applications,":[6],"importance":[8],"of":[9,52,60,72,85,132,145,159],"applying":[10],"deep":[11,40],"learning":[12,41],"to":[13,56],"point":[14],"clouds":[15],"have":[16],"been":[17],"growing":[18],"recently.":[19],"It":[20],"is":[21],"known":[22],"that":[23,82],"mapping":[24,45],"operations":[25,46],"including":[26],"sampling":[27,76],"and":[28,77,80,136,152],"grouping":[29,78],"play":[30],"a":[31,106,124,128],"critical":[32],"role":[33],"in":[34,38,50,148],"extracting":[35],"local":[36],"features":[37],"point-based":[39],"models.":[42],"However,":[43],"often":[47],"become":[48],"bottlenecks":[49],"terms":[51],"computing":[53],"times":[54],"due":[55],"repetitive":[58],"comparison":[59,88,111,116],"distances":[61],"between":[62],"input":[63],"points.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,104],"analyzed":[69],"characteristics":[71],"distance":[73,87,95,129],"distribution":[74],"during":[75],"operations,":[79],"discovered":[81],"substantial":[83],"portion":[84],"does":[89],"not":[90],"need":[91],"exact":[92],"3D":[93,135],"Euclidean":[94],"using":[96],"all":[97],"three":[98],"coordinates.":[99],"Based":[100],"observations,":[103],"propose":[105],"technique":[107],"called":[108],"single":[109],"coordinate":[110],"which":[112],"selectively":[113],"determines":[114],"output":[117],"with":[118,127],"1D-distance":[119],"only.":[120],"We":[121],"also":[122],"present":[123],"hardware":[125],"architecture":[126],"calculator":[130],"capable":[131],"handling":[133],"both":[134,150],"1D":[137],"distance.":[138],"The":[139],"experimental":[140],"results":[141],"demonstrate":[142],"effectiveness":[144],"our":[146],"approach":[147],"reducing":[149],"time":[151],"energy":[153],"consumption,":[154],"particularly":[155],"as":[156],"number":[158],"points":[160],"increases.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
