{"id":"https://openalex.org/W2737368828","doi":"https://doi.org/10.1145/3072959.3073601","title":"Interactive reconstruction of Monte Carlo image sequences using a recurrent denoising autoencoder","display_name":"Interactive reconstruction of Monte Carlo image sequences using a recurrent denoising autoencoder","publication_year":2017,"publication_date":"2017-07-20","ids":{"openalex":"https://openalex.org/W2737368828","doi":"https://doi.org/10.1145/3072959.3073601","mag":"2737368828"},"language":"en","primary_location":{"id":"doi:10.1145/3072959.3073601","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3072959.3073601","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/A5080422360","display_name":"Chakravarty R. Alla Chaitanya","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]},{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chakravarty R. Alla Chaitanya","raw_affiliation_strings":["University of Montreal and McGill University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Montreal and McGill University","institution_ids":["https://openalex.org/I5023651","https://openalex.org/I70931966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014125476","display_name":"Anton Kaplanyan","orcid":"https://orcid.org/0000-0002-8376-6719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anton S. Kaplanyan","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080429609","display_name":"Christoph Schied","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]},{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}],"countries":["DE","GB"],"is_corresponding":false,"raw_author_name":"Christoph Schied","raw_affiliation_strings":["NVIDIA and Karlsruhe Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA and Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020","https://openalex.org/I1304085615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090733850","display_name":"Marco Salvi","orcid":"https://orcid.org/0009-0003-1366-2396"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marco Salvi","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087647732","display_name":"Aaron Lefohn","orcid":"https://orcid.org/0009-0002-6526-0922"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aaron Lefohn","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053824527","display_name":"Derek Nowrouzezahrai","orcid":"https://orcid.org/0000-0002-4279-1774"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Derek Nowrouzezahrai","raw_affiliation_strings":["McGill University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080133323","display_name":"Timo Aila","orcid":"https://orcid.org/0000-0002-9437-4438"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Timo Aila","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.7141,"has_fulltext":false,"cited_by_count":311,"citation_normalized_percentile":{"value":0.99393367,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"36","issue":"4","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991999864578247,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.998199999332428,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7809287309646606},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.711322009563446},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6858017444610596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6023750305175781},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5615904927253723},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5260127782821655},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.504165530204773},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4971976578235626},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46660181879997253},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.45654770731925964},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.43551087379455566},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42907750606536865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15890547633171082}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7809287309646606},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.711322009563446},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6858017444610596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6023750305175781},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5615904927253723},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5260127782821655},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.504165530204773},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4971976578235626},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46660181879997253},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.45654770731925964},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.43551087379455566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42907750606536865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15890547633171082},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3072959.3073601","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3072959.3073601","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310638","display_name":"McGill University","ror":"https://ror.org/01pxwe438"},{"id":"https://openalex.org/F4320334841","display_name":"Fonds de recherche du Qu\u00e9bec \u2013 Nature et technologies","ror":"https://ror.org/00b9f9778"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1165382972","https://openalex.org/W1522301498","https://openalex.org/W1677149932","https://openalex.org/W1776042733","https://openalex.org/W1893585201","https://openalex.org/W1901129140","https://openalex.org/W1937867079","https://openalex.org/W1969679542","https://openalex.org/W1971129545","https://openalex.org/W1971958581","https://openalex.org/W1987844198","https://openalex.org/W1988183349","https://openalex.org/W2001662666","https://openalex.org/W2005081240","https://openalex.org/W2011793254","https://openalex.org/W2020032267","https://openalex.org/W2020681231","https://openalex.org/W2023644015","https://openalex.org/W2025768430","https://openalex.org/W2030126801","https://openalex.org/W2036532817","https://openalex.org/W2037735934","https://openalex.org/W2045422729","https://openalex.org/W2047913565","https://openalex.org/W2050513283","https://openalex.org/W2054640142","https://openalex.org/W2068359544","https://openalex.org/W2076063813","https://openalex.org/W2077323204","https://openalex.org/W2102605133","https://openalex.org/W2102727143","https://openalex.org/W2103607478","https://openalex.org/W2105180255","https://openalex.org/W2108553608","https://openalex.org/W2112796928","https://openalex.org/W2121072877","https://openalex.org/W2125561951","https://openalex.org/W2128540422","https://openalex.org/W2133665775","https://openalex.org/W2138624212","https://openalex.org/W2142380402","https://openalex.org/W2150868589","https://openalex.org/W2152424459","https://openalex.org/W2157298636","https://openalex.org/W2163605009","https://openalex.org/W2168668658","https://openalex.org/W2175030374","https://openalex.org/W2184360182","https://openalex.org/W2261707685","https://openalex.org/W2285660444","https://openalex.org/W2308529009","https://openalex.org/W2384495648","https://openalex.org/W2461158874","https://openalex.org/W2466064361","https://openalex.org/W2471801048","https://openalex.org/W2476548250","https://openalex.org/W2505636029","https://openalex.org/W2552928802","https://openalex.org/W2561076883","https://openalex.org/W2562637781","https://openalex.org/W2738449271","https://openalex.org/W2949608135","https://openalex.org/W2949650786","https://openalex.org/W2951309005","https://openalex.org/W2963420272","https://openalex.org/W2963470893","https://openalex.org/W3007442407","https://openalex.org/W3092513251","https://openalex.org/W4211106717","https://openalex.org/W4211200634","https://openalex.org/W4245933748","https://openalex.org/W4255908685"],"related_works":["https://openalex.org/W2397912953","https://openalex.org/W2124439461","https://openalex.org/W2367434614","https://openalex.org/W3037110488","https://openalex.org/W2099004500","https://openalex.org/W2077708435","https://openalex.org/W4376115546","https://openalex.org/W4243167425","https://openalex.org/W1992884771","https://openalex.org/W4206603469"],"abstract_inverted_index":{"We":[0,62,132],"describe":[1],"a":[2,45,150],"machine":[3],"learning":[4],"technique":[5],"for":[6,64,103,153],"reconstructing":[7],"image":[8,37],"sequences":[9,104],"rendered":[10],"using":[11],"Monte":[12,59],"Carlo":[13,60],"methods.":[14],"Our":[15,84,110],"primary":[16,85],"focus":[17],"is":[18,87],"on":[19,122],"reconstruction":[20],"of":[21,47,55,82,90,105,117],"global":[22],"illumination":[23],"with":[24,39],"extremely":[25],"low":[26],"sampling":[27],"budgets":[28],"at":[29,144,158],"interactive":[30],"rates.":[31],"Motivated":[32],"by":[33,79],"recent":[34],"advances":[35],"in":[36,58,96,161],"restoration":[38],"deep":[40],"convolutional":[41],"networks,":[42],"we":[43],"propose":[44],"variant":[46],"these":[48],"networks":[49],"better":[50],"suited":[51],"to":[52,69,93,98,139],"the":[53,88,94,114,162],"class":[54],"noise":[56],"present":[57],"rendering.":[61],"allow":[63],"much":[65],"larger":[66],"pixel":[67],"neighborhoods":[68],"be":[70],"taken":[71],"into":[72],"account,":[73],"while":[74],"also":[75,112],"improving":[76],"execution":[77],"speed":[78],"an":[80],"order":[81,97],"magnitude.":[83],"contribution":[86],"addition":[89],"recurrent":[91],"connections":[92],"network":[95],"drastically":[99],"improve":[100],"temporal":[101],"stability":[102],"sparsely":[106],"sampled":[107],"input":[108,125],"images.":[109],"method":[111,156],"has":[113],"desirable":[115],"property":[116],"automatically":[118],"modeling":[119],"relationships":[120],"based":[121],"auxiliary":[123],"per-pixel":[124],"channels,":[126],"such":[127],"as":[128],"depth":[129],"and":[130,147],"normals.":[131],"show":[133],"significantly":[134],"higher":[135],"quality":[136],"results":[137],"compared":[138],"existing":[140],"methods":[141],"that":[142],"run":[143,157],"comparable":[145],"speeds,":[146],"furthermore":[148],"argue":[149],"clear":[151],"path":[152],"making":[154],"our":[155],"realtime":[159],"rates":[160],"near":[163],"future.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":59},{"year":2020,"cited_by_count":50},{"year":2019,"cited_by_count":39},{"year":2018,"cited_by_count":26},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
