{"id":"https://openalex.org/W4394867030","doi":"https://doi.org/10.48550/arxiv.2404.09591","title":"3D Gaussian Splatting as Markov Chain Monte Carlo","display_name":"3D Gaussian Splatting as Markov Chain Monte Carlo","publication_year":2024,"publication_date":"2024-04-15","ids":{"openalex":"https://openalex.org/W4394867030","doi":"https://doi.org/10.48550/arxiv.2404.09591"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2404.09591","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.09591","pdf_url":"https://arxiv.org/pdf/2404.09591","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2404.09591","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5105707320","display_name":"Shakiba Kheradmand","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kheradmand, Shakiba","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051106306","display_name":"Daniel Rebain","orcid":"https://orcid.org/0000-0003-4691-7909"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rebain, Daniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090827915","display_name":"G. K. Sharma","orcid":"https://orcid.org/0000-0001-8674-9132"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Gopal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050009113","display_name":"Weiwei Sun","orcid":"https://orcid.org/0000-0003-3399-7858"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Weiwei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105697614","display_name":"Jeff Tseng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tseng, Jeff","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038912082","display_name":"Hossam Isack","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Isack, Hossam","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063644367","display_name":"Abhishek Kar","orcid":"https://orcid.org/0000-0003-2991-6867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kar, Abhishek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037094498","display_name":"Andrea Tagliasacchi","orcid":"https://orcid.org/0000-0002-2209-7187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tagliasacchi, Andrea","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049893251","display_name":"Kwang Moo Yi","orcid":"https://orcid.org/0000-0001-9036-3822"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Kwang Moo","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5105707320"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.05640000104904175,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.05640000104904175,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.6520146727561951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.53836989402771},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5097121596336365},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.49723532795906067},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44804465770721436},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22219574451446533},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18496686220169067},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12670767307281494},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10658910870552063}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6520146727561951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.53836989402771},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5097121596336365},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.49723532795906067},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44804465770721436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22219574451446533},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18496686220169067},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12670767307281494},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10658910870552063},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2404.09591","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.09591","pdf_url":"https://arxiv.org/pdf/2404.09591","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2404.09591","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2404.09591","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2404.09591","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.09591","pdf_url":"https://arxiv.org/pdf/2404.09591","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2151689585","https://openalex.org/W2380816257","https://openalex.org/W3087071515","https://openalex.org/W4283726152","https://openalex.org/W2390279801","https://openalex.org/W1525770572","https://openalex.org/W2358668433","https://openalex.org/W2376932109"],"abstract_inverted_index":{"While":[0],"3D":[1,44,78,104],"Gaussian":[2,79,105],"Splatting":[3,106],"has":[4],"recently":[5],"become":[6],"popular":[7],"for":[8,21],"neural":[9],"rendering,":[10],"current":[11],"methods":[12],"rely":[13],"on":[14,32],"carefully":[15],"engineered":[16],"cloning":[17],"and":[18,30,100,178],"splitting":[19],"strategies":[20,102],"placing":[22],"Gaussians,":[23,145,177],"which":[24],"can":[25,81],"lead":[26],"to":[27,180],"poor-quality":[28],"renderings,":[29],"reliance":[31],"a":[33,47,109,132,148],"good":[34],"initialization.":[35,181],"In":[36],"this":[37,72],"work,":[38],"we":[39,74,125,146,162],"rethink":[40],"the":[41,57,61,77,98,120,127,152,174],"set":[42],"of":[43,60,113,129,144,154,176],"Gaussians":[45,130],"as":[46,84,107],"random":[48],"sample":[49,138],"drawn":[50],"from":[51,119],"an":[52],"underlying":[53],"probability":[54],"distribution":[55],"describing":[56],"physical":[58],"representation":[59],"scene-in":[62],"other":[63],"words,":[64],"Markov":[65],"Chain":[66],"Monte":[67],"Carlo":[68],"(MCMC)":[69],"samples.":[70],"Under":[71],"view,":[73],"show":[75,163],"that":[76,135,150,164],"updates":[80,90],"be":[82],"converted":[83],"Stochastic":[85],"Gradient":[86],"Langevin":[87],"Dynamics":[88],"(SGLD)":[89],"by":[91],"simply":[92,108],"introducing":[93],"noise.":[94],"We":[95],"then":[96],"rewrite":[97],"densification":[99],"pruning":[101],"in":[103],"deterministic":[110],"state":[111],"transition":[112],"MCMC":[114],"samples,":[115],"removing":[116],"these":[117],"heuristics":[118],"framework.":[121],"To":[122,140],"do":[123],"so,":[124],"revise":[126],"'cloning'":[128],"into":[131],"relocalization":[133],"scheme":[134],"approximately":[136],"preserves":[137],"probability.":[139],"encourage":[141],"efficient":[142],"use":[143],"introduce":[147],"regularizer":[149],"promotes":[151],"removal":[153],"unused":[155],"Gaussians.":[156],"On":[157],"various":[158],"standard":[159],"evaluation":[160],"scenes,":[161],"our":[165],"method":[166],"provides":[167],"improved":[168],"rendering":[169],"quality,":[170],"easy":[171],"control":[172],"over":[173],"number":[175],"robustness":[179]},"counts_by_year":[{"year":2025,"cited_by_count":10}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
