{"id":"https://openalex.org/W4387769563","doi":"https://doi.org/10.1145/3629166","title":"Decorrelating ReSTIR Samplers via MCMC Mutations","display_name":"Decorrelating ReSTIR Samplers via MCMC Mutations","publication_year":2023,"publication_date":"2023-10-19","ids":{"openalex":"https://openalex.org/W4387769563","doi":"https://doi.org/10.1145/3629166"},"language":"en","primary_location":{"id":"doi:10.1145/3629166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3629166","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":"hybrid","oa_url":"https://doi.org/10.1145/3629166","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063051822","display_name":"Rohan Sawhney","orcid":"https://orcid.org/0000-0002-3661-1554"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rohan Sawhney","raw_affiliation_strings":["Carnegie Mellon University and NVIDIA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University and NVIDIA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020509011","display_name":"Daqi Lin","orcid":"https://orcid.org/0000-0002-5139-6418"},"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":"Daqi Lin","raw_affiliation_strings":["NVIDIA, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070500994","display_name":"Markus Kettunen","orcid":"https://orcid.org/0000-0002-5206-9603"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Markus Kettunen","raw_affiliation_strings":["NVIDIA, Finland"],"affiliations":[{"raw_affiliation_string":"NVIDIA, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079958610","display_name":"Benedikt Bitterli","orcid":"https://orcid.org/0000-0002-8799-7119"},"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":"Benedikt Bitterli","raw_affiliation_strings":["NVIDIA, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034754633","display_name":"Ravi Ramamoorthi","orcid":"https://orcid.org/0000-0003-3993-5789"},"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"]},{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi Ramamoorthi","raw_affiliation_strings":["NVIDIA and UC San Diego, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA and UC San Diego, USA","institution_ids":["https://openalex.org/I4210127875","https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006219693","display_name":"Chris Wyman","orcid":"https://orcid.org/0000-0002-5133-4292"},"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":"Chris Wyman","raw_affiliation_strings":["NVIDIA, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102003967","display_name":"Matt Pharr","orcid":"https://orcid.org/0000-0002-0566-8291"},"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":"Matt Pharr","raw_affiliation_strings":["NVIDIA, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA, USA","institution_ids":["https://openalex.org/I4210127875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5063051822"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":4.4324,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.95977809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"43","issue":"1","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9976999759674072,"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":0.9976999759674072,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9947999715805054,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.992900013923645,"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/resampling","display_name":"Resampling","score":0.8584046363830566},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8022596836090088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6890996694564819},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5959309935569763},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5806277394294739},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.5508319735527039},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5226238369941711},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5165852308273315},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.41577237844467163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4057428240776062},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3876839876174927},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2279537320137024},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22443801164627075},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21076041460037231},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.16022133827209473}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.8584046363830566},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8022596836090088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6890996694564819},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5959309935569763},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5806277394294739},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.5508319735527039},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5226238369941711},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5165852308273315},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.41577237844467163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4057428240776062},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3876839876174927},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2279537320137024},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22443801164627075},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21076041460037231},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.16022133827209473},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3629166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3629166","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3629166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3629166","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1483307070","https://openalex.org/W1513873506","https://openalex.org/W1546027711","https://openalex.org/W1551583610","https://openalex.org/W1797096580","https://openalex.org/W1965744692","https://openalex.org/W1966671941","https://openalex.org/W1979969656","https://openalex.org/W2021131939","https://openalex.org/W2038630728","https://openalex.org/W2038974043","https://openalex.org/W2045555847","https://openalex.org/W2046872971","https://openalex.org/W2056760934","https://openalex.org/W2131413095","https://openalex.org/W2135002170","https://openalex.org/W2138309709","https://openalex.org/W2142380402","https://openalex.org/W2147357149","https://openalex.org/W2151035893","https://openalex.org/W2257275871","https://openalex.org/W2609525154","https://openalex.org/W2737368828","https://openalex.org/W2888636902","https://openalex.org/W2900078869","https://openalex.org/W2902692665","https://openalex.org/W2906842388","https://openalex.org/W2911851818","https://openalex.org/W2912424718","https://openalex.org/W2912627705","https://openalex.org/W2912892010","https://openalex.org/W2913844511","https://openalex.org/W2914784861","https://openalex.org/W2979652999","https://openalex.org/W3086190093","https://openalex.org/W3090531178","https://openalex.org/W3099553476","https://openalex.org/W3195014170","https://openalex.org/W3197966214","https://openalex.org/W4200169191","https://openalex.org/W4206352693","https://openalex.org/W4231407972","https://openalex.org/W4245933748","https://openalex.org/W4250753557","https://openalex.org/W6888747901"],"related_works":["https://openalex.org/W2397912953","https://openalex.org/W2124439461","https://openalex.org/W2367434614","https://openalex.org/W2099004500","https://openalex.org/W4206603469","https://openalex.org/W4388994528","https://openalex.org/W2077708435","https://openalex.org/W4376115546","https://openalex.org/W1992884771","https://openalex.org/W4281488350"],"abstract_inverted_index":{"Monte":[0,109],"Carlo":[1,110],"rendering":[2],"algorithms":[3],"often":[4,82],"utilize":[5],"correlations":[6],"between":[7],"pixels":[8],"to":[9,28,47],"improve":[10],"efficiency":[11],"and":[12,36,59,126,137],"enhance":[13],"image":[14,35,145],"quality.":[15],"For":[16,78],"real-time":[17,51],"applications":[18],"in":[19,33,97,121,138,144,155],"particular,":[20],"repeated":[21],"reservoir":[22,114,153],"resampling":[23,81,115],"offers":[24],"a":[25,149],"powerful":[26],"framework":[27],"reuse":[29],"samples":[30],"both":[31],"spatially":[32],"an":[34],"temporally":[37],"across":[38],"multiple":[39],"frames.":[40],"While":[41],"such":[42],"techniques":[43],"achieve":[44],"equal-error":[45],"up":[46],"100\u00d7":[48],"faster":[49],"for":[50],"direct":[52],"lighting":[53],"[Bitterli":[54],"et":[55,63,68],"al.":[56,64,69],"2020":[57],"]":[58],"global":[60],"illumination":[61],"[Ouyang":[62],"2021":[65,70],";":[66],"Lin":[67],"],":[71],"they":[72],"are":[73],"still":[74],"far":[75],"from":[76,95],"optimal.":[77],"instance,":[79],"spatiotemporal":[80],"introduces":[83],"noticeable":[84],"correlation":[85],"artifacts,":[86],"while":[87],"reservoirs":[88],"holding":[89],"more":[90],"than":[91],"one":[92],"sample":[93,154],"suffer":[94],"impoverishment":[96],"the":[98],"form":[99],"of":[100],"duplicate":[101],"samples.":[102],"We":[103],"demonstrate":[104],"how":[105],"interleaving":[106],"Markov":[107],"Chain":[108],"(MCMC)":[111],"mutations":[112],"with":[113,123,147],"helps":[116],"alleviate":[117],"these":[118],"issues,":[119],"especially":[120],"scenes":[122],"glossy":[124],"materials":[125],"difficult-to-sample":[127],"lighting.":[128],"Moreover,":[129],"our":[130],"approach":[131],"does":[132],"not":[133],"introduce":[134],"any":[135],"bias,":[136],"practice,":[139],"we":[140],"find":[141],"considerable":[142],"improvement":[143],"quality":[146],"just":[148],"single":[150],"mutation":[151],"per":[152],"each":[156],"frame.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}