{"id":"https://openalex.org/W4404965689","doi":"https://doi.org/10.1145/3680528.3687622","title":"Markov-Chain Monte Carlo Sampling of Visibility Boundaries for Differentiable Rendering","display_name":"Markov-Chain Monte Carlo Sampling of Visibility Boundaries for Differentiable Rendering","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4404965689","doi":"https://doi.org/10.1145/3680528.3687622"},"language":"en","primary_location":{"id":"doi:10.1145/3680528.3687622","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680528.3687622","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680528.3687622","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2024 Conference Papers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3680528.3687622","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042112217","display_name":"Peiyu Xu","orcid":"https://orcid.org/0009-0007-0271-2545"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peiyu Xu","raw_affiliation_strings":["University of California Irvine, Irvine, United States of America"],"raw_orcid":"https://orcid.org/0009-0007-0271-2545","affiliations":[{"raw_affiliation_string":"University of California Irvine, Irvine, United States of America","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090575298","display_name":"Sai Praveen Bangaru","orcid":"https://orcid.org/0000-0001-6302-9327"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sai Bangaru","raw_affiliation_strings":["MIT CSAIL, Cambridge, United States of America"],"raw_orcid":"https://orcid.org/0000-0001-6302-9327","affiliations":[{"raw_affiliation_string":"MIT CSAIL, Cambridge, United States of America","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030293104","display_name":"Tzu\u2010Mao Li","orcid":"https://orcid.org/0000-0001-5443-470X"},"institutions":[{"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":"Tzu-Mao Li","raw_affiliation_strings":["University of California San Diego, San Diego, United States of America"],"raw_orcid":"https://orcid.org/0000-0001-5443-470X","affiliations":[{"raw_affiliation_string":"University of California San Diego, San Diego, United States of America","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057808448","display_name":"Shuang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuang Zhao","raw_affiliation_strings":["University of California Irvine, Irvine, United States of America"],"raw_orcid":"https://orcid.org/0000-0003-4759-0514","affiliations":[{"raw_affiliation_string":"University of California Irvine, Irvine, United States of America","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042112217"],"corresponding_institution_ids":["https://openalex.org/I204250578"],"apc_list":null,"apc_paid":null,"fwci":1.8025,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.91786315,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9944000244140625,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7464134693145752},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.634971559047699},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6206923127174377},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.616214394569397},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.48257341980934143},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.41868042945861816},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.4043257534503937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2330794632434845},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2031257152557373},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18217942118644714},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.16307970881462097},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11787617206573486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10929462313652039}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7464134693145752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634971559047699},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6206923127174377},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.616214394569397},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.48257341980934143},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.41868042945861816},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.4043257534503937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2330794632434845},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2031257152557373},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18217942118644714},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.16307970881462097},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11787617206573486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10929462313652039}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3680528.3687622","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680528.3687622","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680528.3687622","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2024 Conference Papers","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/158126","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/158126","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/158126/1/3680528.3687622.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Association for Computing Machinery","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"doi:10.1145/3680528.3687622","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3680528.3687622","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3680528.3687622","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2024 Conference Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3101190323","display_name":null,"funder_award_id":"2105806","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4404965689.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W621546036","https://openalex.org/W1666661718","https://openalex.org/W1966671941","https://openalex.org/W1983452151","https://openalex.org/W2008693968","https://openalex.org/W2059069038","https://openalex.org/W2059448777","https://openalex.org/W2135002170","https://openalex.org/W2135973421","https://openalex.org/W2142380402","https://openalex.org/W2151035893","https://openalex.org/W2900162369","https://openalex.org/W2902692665","https://openalex.org/W2902812770","https://openalex.org/W2985626319","https://openalex.org/W2986486518","https://openalex.org/W2986860185","https://openalex.org/W3048916779","https://openalex.org/W3099553476","https://openalex.org/W3106721722","https://openalex.org/W3183537987","https://openalex.org/W4206705894","https://openalex.org/W4212774754","https://openalex.org/W4229995614","https://openalex.org/W4241602464","https://openalex.org/W4246464108","https://openalex.org/W4247880210","https://openalex.org/W4286611307","https://openalex.org/W4286615931","https://openalex.org/W4311034047","https://openalex.org/W4311806037","https://openalex.org/W4385534306","https://openalex.org/W4389334925","https://openalex.org/W4389339346","https://openalex.org/W4389348974","https://openalex.org/W4389539688","https://openalex.org/W4392003939","https://openalex.org/W4400821989"],"related_works":["https://openalex.org/W2305965628","https://openalex.org/W4226314133","https://openalex.org/W1548972748","https://openalex.org/W3186706744","https://openalex.org/W3192708935","https://openalex.org/W227870709","https://openalex.org/W4294677683","https://openalex.org/W2959831473","https://openalex.org/W4323055853","https://openalex.org/W2291370119"],"abstract_inverted_index":{"SA":[0],"Conference":[1],"Papers":[2],"\u201924,":[3],"December":[4],"03\u201306,":[5],"2024,":[6],"Tokyo,":[7],"Japan":[8]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
