{"id":"https://openalex.org/W2011793254","doi":"https://doi.org/10.1145/2766992","title":"Adaptive rendering with linear predictions","display_name":"Adaptive rendering with linear predictions","publication_year":2015,"publication_date":"2015-07-27","ids":{"openalex":"https://openalex.org/W2011793254","doi":"https://doi.org/10.1145/2766992","mag":"2011793254"},"language":"en","primary_location":{"id":"doi:10.1145/2766992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2766992","pdf_url":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085021305","display_name":"Bochang Moon","orcid":"https://orcid.org/0000-0003-3142-0115"},"institutions":[{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bochang Moon","raw_affiliation_strings":["Disney Research Z\u00fcrich"],"affiliations":[{"raw_affiliation_string":"Disney Research Z\u00fcrich","institution_ids":["https://openalex.org/I4210142140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007041759","display_name":"Jos\u00e9 A. Iglesias-Guiti\u00e1n","orcid":"https://orcid.org/0000-0002-0817-1010"},"institutions":[{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jose A. Iglesias-Guitian","raw_affiliation_strings":["Disney Research Z\u00fcrich"],"affiliations":[{"raw_affiliation_string":"Disney Research Z\u00fcrich","institution_ids":["https://openalex.org/I4210142140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078173428","display_name":"Sung\u2010Eui Yoon","orcid":"https://orcid.org/0000-0002-7123-1119"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR","US"],"is_corresponding":false,"raw_author_name":"Sung-Eui Yoon","raw_affiliation_strings":["KAIST","Disney Enterprises, Inc. (Burbank, CA, US)"],"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I4210099236","https://openalex.org/I157485424"]},{"raw_affiliation_string":"Disney Enterprises, Inc. (Burbank, CA, US)","institution_ids":["https://openalex.org/I4210142140"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025634364","display_name":"Kenny Mitchell","orcid":"https://orcid.org/0000-0003-2420-7447"},"institutions":[{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenny Mitchell","raw_affiliation_strings":["Disney Research Z\u00fcrich"],"affiliations":[{"raw_affiliation_string":"Disney Research Z\u00fcrich","institution_ids":["https://openalex.org/I4210142140"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085021305"],"corresponding_institution_ids":["https://openalex.org/I4210142140"],"apc_list":null,"apc_paid":null,"fwci":15.818,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.99203848,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"34","issue":"4","first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.7539702653884888},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7034692764282227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6984924077987671},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.543688178062439},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.5266870260238647},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.46344590187072754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4528036415576935},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.4248966574668884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1154600977897644}],"concepts":[{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.7539702653884888},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7034692764282227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984924077987671},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.543688178062439},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.5266870260238647},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.46344590187072754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4528036415576935},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.4248966574668884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1154600977897644}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2766992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2766992","pdf_url":null,"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"},{"id":"pmh:oai:napier-surface.worktribe.com:951621","is_oa":false,"landing_page_url":"http://researchrepository.napier.ac.uk/Output/951621","pdf_url":null,"source":{"id":"https://openalex.org/S4306400544","display_name":"Research Output (Edinburgh Napier University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I251738","host_organization_name":"Edinburgh Napier University","host_organization_lineage":["https://openalex.org/I251738"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W174441044","https://openalex.org/W1540723801","https://openalex.org/W1566696021","https://openalex.org/W1680392829","https://openalex.org/W1937466823","https://openalex.org/W1965744692","https://openalex.org/W1969885994","https://openalex.org/W1971958581","https://openalex.org/W1972815766","https://openalex.org/W1977778188","https://openalex.org/W1984696318","https://openalex.org/W2030126801","https://openalex.org/W2034080786","https://openalex.org/W2036532817","https://openalex.org/W2037735934","https://openalex.org/W2050297026","https://openalex.org/W2050513283","https://openalex.org/W2056678683","https://openalex.org/W2066476997","https://openalex.org/W2082211440","https://openalex.org/W2096500711","https://openalex.org/W2105180255","https://openalex.org/W2113288858","https://openalex.org/W2115373434","https://openalex.org/W2116671147","https://openalex.org/W2125561951","https://openalex.org/W2138624212","https://openalex.org/W2139189324","https://openalex.org/W2150868589","https://openalex.org/W2157298636","https://openalex.org/W2165652511","https://openalex.org/W2207744012","https://openalex.org/W2409793996","https://openalex.org/W2525786140","https://openalex.org/W3007442407","https://openalex.org/W3015136933","https://openalex.org/W3137870839","https://openalex.org/W4210697527","https://openalex.org/W4237407156"],"related_works":["https://openalex.org/W2397912953","https://openalex.org/W2124439461","https://openalex.org/W2367434614","https://openalex.org/W2099004500","https://openalex.org/W4388994528","https://openalex.org/W2077708435","https://openalex.org/W4376115546","https://openalex.org/W4243167425","https://openalex.org/W1992884771","https://openalex.org/W4206603469"],"abstract_inverted_index":{"We":[0,163,192],"propose":[1],"a":[2,24,33,125,138,177],"new":[3],"adaptive":[4,190],"rendering":[5,185],"algorithm":[6],"that":[7,67,195],"enhances":[8],"the":[9,18,58,62,99,131,161],"performance":[10,206],"of":[11,26,75,128],"Monte":[12],"Carlo":[13],"ray":[14,207],"tracing":[15,208],"by":[16,84],"reducing":[17],"noise,":[19],"i.e.,":[20],"variance,":[21],"while":[22],"preserving":[23],"variety":[25],"high-frequency":[27],"edges":[28],"in":[29,130,160],"rendered":[30],"images":[31],"through":[32],"novel":[34],"prediction":[35,55,81,90,96,115],"based":[36],"reconstruction.":[37],"To":[38],"achieve":[39],"our":[40,120,169,196],"goal,":[41],"we":[42,117],"iteratively":[43],"build":[44],"multiple,":[45],"but":[46],"sparse":[47,126],"linear":[48,51,59,85,103,107,121,140],"models.":[49],"Each":[50],"model":[52,60,108,141],"has":[53,156],"its":[54,113],"window,":[56],"where":[57],"predicts":[61,109],"unknown":[63],"ground":[64],"truth":[65],"image":[66,132],"can":[68,118],"be":[69],"generated":[70],"with":[71,88,137,171,183,204],"an":[72,94],"infinite":[73],"number":[74],"samples.":[76],"Our":[77],"method":[78,170,197],"recursively":[79],"estimates":[80],"errors":[82],"introduced":[83],"predictions":[86],"performed":[87],"different":[89],"windows,":[91],"and":[92,155,168,202,213],"selects":[93],"optimal":[95,114],"window":[97],"minimizing":[98],"error":[100,148,173],"for":[101,150],"each":[102,106],"model.":[104],"Since":[105],"multiple":[110,135],"pixels":[111,129,136],"within":[112],"interval,":[116],"construct":[119],"models":[122],"only":[123],"at":[124],"set":[127],"screen.":[133],"Predicting":[134],"single":[139],"poses":[142],"technical":[143,166],"challenges,":[144,167],"related":[145],"to":[146,176,188],"deriving":[147],"analysis":[149,174],"regions":[151],"rather":[152],"than":[153],"pixels,":[154],"not":[157],"been":[158],"addressed":[159],"field.":[162],"address":[164],"these":[165],"robust":[172],"leads":[175],"drastically":[178],"reduced":[179],"reconstruction":[180],"time":[181],"even":[182],"higher":[184],"quality,":[186],"compared":[187],"state-of-the-art":[189],"methods.":[191],"have":[193],"demonstrated":[194],"outperforms":[198],"previous":[199],"methods":[200],"numerically":[201],"visually":[203],"high":[205],"kernels":[209],"such":[210],"as":[211],"OptiX":[212],"Embree.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}