{"id":"https://openalex.org/W4391136367","doi":"https://doi.org/10.1145/3641817","title":"NeuralVDB: High-resolution Sparse Volume Representation using Hierarchical Neural Networks","display_name":"NeuralVDB: High-resolution Sparse Volume Representation using Hierarchical Neural Networks","publication_year":2024,"publication_date":"2024-01-23","ids":{"openalex":"https://openalex.org/W4391136367","doi":"https://doi.org/10.1145/3641817"},"language":"en","primary_location":{"id":"doi:10.1145/3641817","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641817","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3641817","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3641817","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036448571","display_name":"Doyub Kim","orcid":"https://orcid.org/0000-0002-8932-5519"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Doyub Kim","raw_affiliation_strings":["NVIDIA, Santa Clara, USA"],"raw_orcid":"https://orcid.org/0000-0002-8932-5519","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449738","display_name":"Minjae Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minjae Lee","raw_affiliation_strings":["NVIDIA, Santa Clara, USA"],"raw_orcid":"https://orcid.org/0009-0003-6387-1081","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034723250","display_name":"Ken Museth","orcid":"https://orcid.org/0000-0002-9926-780X"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ken Museth","raw_affiliation_strings":["NVIDIA, Santa Clara, USA"],"raw_orcid":"https://orcid.org/0000-0002-9926-780X","affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, USA","institution_ids":["https://openalex.org/I4210127875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210127875"],"apc_list":null,"apc_paid":null,"fwci":19.6008,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.99352971,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"43","issue":"2","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9995999932289124,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9983000159263611,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/volume","display_name":"Volume (thermodynamics)","score":0.6309114694595337},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6199054718017578},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6113592982292175},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.536597490310669},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48196837306022644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4722553789615631},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.44026055932044983},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3499739170074463},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3206602931022644}],"concepts":[{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6309114694595337},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6199054718017578},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6113592982292175},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.536597490310669},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48196837306022644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4722553789615631},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.44026055932044983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3499739170074463},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3206602931022644},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641817","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641817","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3641817","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3641817","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641817","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3641817","source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391136367.pdf","grobid_xml":"https://content.openalex.org/works/W4391136367.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1981382127","https://openalex.org/W2012541063","https://openalex.org/W2029315739","https://openalex.org/W2060863649","https://openalex.org/W2061782157","https://openalex.org/W2070071217","https://openalex.org/W2089266499","https://openalex.org/W2099342750","https://openalex.org/W2101560656","https://openalex.org/W2108891011","https://openalex.org/W2115907784","https://openalex.org/W2117028583","https://openalex.org/W2128943711","https://openalex.org/W2166819598","https://openalex.org/W2170258208","https://openalex.org/W2526807362","https://openalex.org/W2558708291","https://openalex.org/W2750023899","https://openalex.org/W2792447253","https://openalex.org/W2794119162","https://openalex.org/W2809090039","https://openalex.org/W2902290465","https://openalex.org/W2902563172","https://openalex.org/W2905188570","https://openalex.org/W2913844511","https://openalex.org/W2935381027","https://openalex.org/W2962771342","https://openalex.org/W2962849139","https://openalex.org/W2963627347","https://openalex.org/W2963926543","https://openalex.org/W2964305533","https://openalex.org/W2979652999","https://openalex.org/W2989630530","https://openalex.org/W3034754560","https://openalex.org/W3036843665","https://openalex.org/W3090763252","https://openalex.org/W3106552726","https://openalex.org/W3109585842","https://openalex.org/W3117476483","https://openalex.org/W3138058008","https://openalex.org/W3176368002","https://openalex.org/W3176679482","https://openalex.org/W3179416528","https://openalex.org/W3181576318","https://openalex.org/W3184957317","https://openalex.org/W3187556994","https://openalex.org/W4210974115","https://openalex.org/W4214564891","https://openalex.org/W4221151978","https://openalex.org/W4283034080","https://openalex.org/W4297846303","https://openalex.org/W6684596909"],"related_works":["https://openalex.org/W2798121181","https://openalex.org/W2016805743","https://openalex.org/W4242592912","https://openalex.org/W435830328","https://openalex.org/W2087896742","https://openalex.org/W2062195135","https://openalex.org/W1989025965","https://openalex.org/W2328676785","https://openalex.org/W2322380964","https://openalex.org/W1517180214"],"abstract_inverted_index":{"We":[0],"introduce":[1],"NeuralVDB,":[2],"which":[3],"improves":[4],"on":[5,125],"an":[6],"existing":[7],"industry":[8],"standard":[9],"for":[10],"efficient":[11],"storage":[12],"of":[13,39,44,63,85,128,165,204,213],"sparse":[14,113],"volumetric":[15],"data,":[16],"denoted":[17],"VDB":[18,40,68,109,137],"[Museth":[19],"2013":[20],"],":[21,171,180],"by":[22,42,83,106],"leveraging":[23],"recent":[24],"advancements":[25],"in":[26],"machine":[27],"learning.":[28],"Our":[29],"novel":[30],"hybrid":[31],"data":[32,110],"structure":[33,70],"can":[34,199],"reduce":[35],"the":[36,60,97,102,107,126],"memory":[37],"footprints":[38],"volumes":[41,206],"orders":[43],"magnitude,":[45],"while":[46,100],"maintaining":[47,101],"its":[48],"flexibility":[49],"and":[50,66,80,88,117,181],"only":[51],"incurring":[52],"small":[53],"(user-controlled)":[54],"compression":[55,98,123,153],"errors.":[56],"Specifically,":[57],"NeuralVDB":[58,146],"replaces":[59],"lower":[61],"nodes":[62],"a":[64],"shallow":[65],"wide":[67],"tree":[69],"with":[71,139],"multiple":[72],"hierarchical":[73],"neural":[74,86,158],"networks":[75],"that":[76],"separately":[77],"encode":[78],"topology":[79],"value":[81],"information":[82],"means":[84],"classifiers":[87],"regressors":[89],"respectively.":[90],"This":[91],"approach":[92],"is":[93,147],"proven":[94],"to":[95,130,141,149,156],"maximize":[96],"ratio":[99],"spatial":[103],"adaptivity":[104],"offered":[105],"higher-level":[108],"structure.":[111],"For":[112],"signed":[114],"distance":[115],"fields":[116],"density":[118],"volumes,":[119],"we":[120,192],"have":[121],"observed":[122],"ratios":[124],"order":[127],"10\u00d7":[129],"more":[131,151],"than":[132],"100\u00d7":[133],"from":[134,196],"already":[135],"compressed":[136],"inputs,":[138],"little":[140],"no":[142],"visual":[143],"artifacts.":[144],"Furthermore,":[145],"shown":[148],"offer":[150],"effective":[152],"performance":[154],"compared":[155],"other":[157],"representations":[159],"such":[160],"as":[161,207,209],"Neural":[162,174,183],"Geometric":[163],"Level":[164],"Detail":[166],"[Takikawa":[167,176],"et":[168,177,187],"al.":[169,178,188],"2021":[170],"Variable":[172],"Bitrate":[173],"Fields":[175],"2022a":[179],"Instant":[182],"Graphics":[184],"Primitives":[185],"[M\u00fcller":[186],"2022":[189],"].":[190],"Finally,":[191],"demonstrate":[193],"how":[194],"warm-starting":[195],"previous":[197],"frames":[198],"accelerate":[200],"training,":[201],"i.e.,":[202,216],"compression,":[203],"animated":[205],"well":[208],"improve":[210],"temporal":[211],"coherency":[212],"model":[214],"inference,":[215],"decompression.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}
