{"id":"https://openalex.org/W2798640928","doi":"https://doi.org/10.1109/cvpr.2018.00694","title":"Discovering Point Lights with Intensity Distance Fields","display_name":"Discovering Point Lights with Intensity Distance Fields","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2798640928","doi":"https://doi.org/10.1109/cvpr.2018.00694","mag":"2798640928"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2018.00694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-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/A5103347003","display_name":"Michael F. Cohen","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Michael F. Cohen","raw_affiliation_strings":["University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028018814","display_name":"Edward Zhang","orcid":"https://orcid.org/0000-0003-3717-1367"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edward Zhang","raw_affiliation_strings":["Facebook, Inc., Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Facebook, Inc., Seattle, WA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011858791","display_name":"Brian Curless","orcid":"https://orcid.org/0000-0002-0095-5400"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Curless","raw_affiliation_strings":["University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103347003"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.8357,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78237206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":null,"first_page":"6635","last_page":"6643"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9988999962806702,"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/computer-vision","display_name":"Computer vision","score":0.7199094295501709},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6714362502098083},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6253064870834351},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6168212890625},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5952489972114563},{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.5653854608535767},{"id":"https://openalex.org/keywords/light-intensity","display_name":"Light intensity","score":0.42622458934783936},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3658778667449951},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29074206948280334},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.24492201209068298},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.19382137060165405},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16410133242607117}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7199094295501709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6714362502098083},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6253064870834351},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6168212890625},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5952489972114563},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.5653854608535767},{"id":"https://openalex.org/C3020368824","wikidata":"https://www.wikidata.org/wiki/Q6546192","display_name":"Light intensity","level":2,"score":0.42622458934783936},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3658778667449951},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29074206948280334},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.24492201209068298},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.19382137060165405},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16410133242607117},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2018.00694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5899999737739563,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310094","display_name":"University of Washington","ror":"https://ror.org/00cvxb145"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1511839063","https://openalex.org/W1557430260","https://openalex.org/W1595337755","https://openalex.org/W1914524668","https://openalex.org/W1973660841","https://openalex.org/W2013223757","https://openalex.org/W2020429267","https://openalex.org/W2026374239","https://openalex.org/W2051740346","https://openalex.org/W2055465094","https://openalex.org/W2069691420","https://openalex.org/W2116143083","https://openalex.org/W2116407716","https://openalex.org/W2123302273","https://openalex.org/W2129404650","https://openalex.org/W2134915967","https://openalex.org/W2145178170","https://openalex.org/W2152005177","https://openalex.org/W2153079591","https://openalex.org/W2163698597","https://openalex.org/W2168922899","https://openalex.org/W2288973411","https://openalex.org/W2296136972","https://openalex.org/W2319845720","https://openalex.org/W2519384515","https://openalex.org/W2536711507","https://openalex.org/W2542741462","https://openalex.org/W2554602114","https://openalex.org/W2584247549","https://openalex.org/W2973948937","https://openalex.org/W4229523108","https://openalex.org/W4239233650","https://openalex.org/W4242043217","https://openalex.org/W6630744482","https://openalex.org/W6635735891","https://openalex.org/W6655190778","https://openalex.org/W6657064701","https://openalex.org/W6679232835","https://openalex.org/W6684221253","https://openalex.org/W6726732716","https://openalex.org/W6732986855"],"related_works":["https://openalex.org/W2794789911","https://openalex.org/W4298134547","https://openalex.org/W2122976425","https://openalex.org/W2088773039","https://openalex.org/W4382753160","https://openalex.org/W2284229495","https://openalex.org/W1994881304","https://openalex.org/W2028697747","https://openalex.org/W4320084277","https://openalex.org/W1990572073"],"abstract_inverted_index":{"We":[0,44,73],"introduce":[1],"the":[2,19,26,28,36,42,75],"light":[3,29,53,71],"localization":[4,30],"problem.":[5],"A":[6],"scene":[7,48],"is":[8,32],"illuminated":[9],"by":[10],"a":[11,47,81],"set":[12,83],"of":[13,25,41,77,84],"unobserved":[14],"isotropic":[15],"point":[16],"lights.":[17,43],"Given":[18],"geometry,":[20],"materials,":[21],"and":[22,39,68,88,99],"illuminated,":[23],"appearance":[24],"scene,":[27],"problem":[31],"to":[33,64,93],"completely":[34],"recover":[35],"number,":[37],"positions,":[38],"intensities":[40],"first":[45],"present":[46],"transform":[49],"that":[50,90],"identifies":[51],"likely":[52],"positions.":[54],"Based":[55],"on":[56],"this":[57,78],"transform,":[58],"we":[59],"develop":[60],"an":[61],"iterative":[62],"algorithm":[63],"locate":[65],"remaining":[66],"lights":[67],"determine":[69],"all":[70],"intensities.":[72],"demonstrate":[74],"success":[76],"method":[79],"in":[80,95],"large":[82],"2D":[85],"synthetic":[86,97],"scenes,":[87],"show":[89],"it":[91],"extends":[92],"3D,":[94],"both":[96],"scenes":[98],"real-world":[100],"scenes.":[101]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}