{"id":"https://openalex.org/W2768807990","doi":"https://doi.org/10.1145/3145690.3145725","title":"DeepHolo","display_name":"DeepHolo","publication_year":2017,"publication_date":"2017-11-20","ids":{"openalex":"https://openalex.org/W2768807990","doi":"https://doi.org/10.1145/3145690.3145725","mag":"2768807990"},"language":"en","primary_location":{"id":"doi:10.1145/3145690.3145725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3145690.3145725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2017 Posters","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/A5075852261","display_name":"Naoya Muramatsu","orcid":"https://orcid.org/0000-0002-8976-2292"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Naoya Muramatsu","raw_affiliation_strings":["University of Tsukuba"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009894158","display_name":"Chun Wei Ooi","orcid":"https://orcid.org/0000-0002-1517-8755"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chun Wei Ooi","raw_affiliation_strings":["University of Tsukuba"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053612507","display_name":"Yuta Itoh","orcid":"https://orcid.org/0000-0002-5901-797X"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuta Itoh","raw_affiliation_strings":["University of Tsukuba"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013807777","display_name":"Yoichi Ochiai","orcid":"https://orcid.org/0000-0002-4690-5724"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoichi Ochiai","raw_affiliation_strings":["University of Tsukuba"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075852261"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":0.4802,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6436969,"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":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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":0.9986000061035156,"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":0.81549072265625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8015239238739014},{"id":"https://openalex.org/keywords/holography","display_name":"Holography","score":0.7008984088897705},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6986644268035889},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6471458077430725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6137534976005554},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.606562614440918},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5544037818908691},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5264735221862793},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4391748607158661},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4234049320220947},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4125773012638092},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4015347361564636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06729963421821594}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.81549072265625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015239238739014},{"id":"https://openalex.org/C187590223","wikidata":"https://www.wikidata.org/wiki/Q527628","display_name":"Holography","level":2,"score":0.7008984088897705},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6986644268035889},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6471458077430725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6137534976005554},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.606562614440918},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5544037818908691},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5264735221862793},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4391748607158661},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4234049320220947},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4125773012638092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4015347361564636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06729963421821594},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3145690.3145725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3145690.3145725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2017 Posters","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1644641054","https://openalex.org/W1920022804","https://openalex.org/W2097117768","https://openalex.org/W2211722331","https://openalex.org/W2339077268","https://openalex.org/W2560609797","https://openalex.org/W2622479542","https://openalex.org/W2962731536","https://openalex.org/W4236965008"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W3009369890","https://openalex.org/W2707254711","https://openalex.org/W2387232132"],"abstract_inverted_index":{"Three-dimensions":[0],"(3D)":[1],"models":[2],"contain":[3],"a":[4,92,115,119,123,156],"wealth":[5],"of":[6,31,53,82,95,108,122],"information":[7,83],"about":[8],"every":[9],"object":[10,125,138],"in":[11,28,130],"our":[12,153],"universe.":[13],"However,":[14],"it":[15,60,113],"is":[16,76,103],"difficult":[17],"to":[18,61,91,105,118,126],"semantically":[19],"recognize":[20,106],"the":[21,35,70,127,131],"media":[22],"forms,":[23],"even":[24],"when":[25],"they":[26],"featured":[27],"simplest":[29],"form":[30],"objects.":[32],"We":[33,68,151],"propose":[34],"DeepHolo":[36,133],"network":[37,50,71,134],"using":[38,72,146],"binary-weighted":[39],"computer-generated":[40],"holograms":[41,107],"(CGHs)":[42],"reconstructed":[43],"from":[44],"point":[45,55,86,116],"cloud":[46,56,87],"models.":[47],"This":[48],"neural":[49],"facilitates":[51],"manipulation":[52],"3D":[54,109,120,144],"form,":[57],"and":[58,78,161],"allows":[59,135],"be":[62],"processed":[63],"as":[64,140,142],"Two-dimensions":[65],"(2D)":[66],"data.":[67],"construct":[69],"hologram":[73],"data,":[74],"which":[75],"simpler":[77],"contains":[79],"smaller":[80,93],"volume":[81],"than":[84],"their":[85],"data(PCD)":[88],"counterpart,":[89],"leading":[90],"number":[94],"parameters":[96],"required.":[97],"The":[98],"Deep":[99],"Neural":[100],"Network":[101],"(DNN)":[102],"trained":[104],"objects,":[110],"so":[111],"that":[112],"resembles":[114],"attributed":[117],"model":[121],"similar":[124],"one":[128],"depicted":[129],"hologram.":[132],"high":[136],"precision":[137],"recognition,":[139],"well":[141],"processing":[143],"data":[145],"much":[147],"lesser":[148],"computer":[149],"resources.":[150],"evaluate":[152],"method":[154],"on":[155],"recognition":[157],"task":[158],"space":[159],"efficiency,":[160],"outperforming":[162],"state-of-the-art":[163],"methods.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2017-12-04T00:00:00"}
