{"id":"https://openalex.org/W2587675858","doi":"https://doi.org/10.1109/iccv.2017.340","title":"Detailed Surface Geometry and Albedo Recovery from RGB-D Video under Natural Illumination","display_name":"Detailed Surface Geometry and Albedo Recovery from RGB-D Video under Natural Illumination","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2587675858","doi":"https://doi.org/10.1109/iccv.2017.340","mag":"2587675858"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","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/A5018096364","display_name":"Xinxin Zuo","orcid":"https://orcid.org/0000-0002-7116-9634"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Xinxin Zuo","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, P.R. China","University of Kentucky, Lexington, KY, US"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, P.R. China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"University of Kentucky, Lexington, KY, US","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350738","display_name":"Sen Wang","orcid":"https://orcid.org/0000-0002-1808-5239"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Sen Wang","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, P.R. China","University of Kentucky, Lexington, KY, US"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, P.R. China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"University of Kentucky, Lexington, KY, US","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100680275","display_name":"Jiangbin Zheng","orcid":"https://orcid.org/0000-0001-5249-2148"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangbin Zheng","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, P.R. China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, P.R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076524203","display_name":"Ruigang Yang","orcid":"https://orcid.org/0000-0001-5296-6307"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Ruigang Yang","raw_affiliation_strings":["Baidu, Beijing, P.R. China","University of Kentucky, Lexington, KY, US"],"affiliations":[{"raw_affiliation_string":"Baidu, Beijing, P.R. China","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"University of Kentucky, Lexington, KY, US","institution_ids":["https://openalex.org/I143302722"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018096364"],"corresponding_institution_ids":["https://openalex.org/I143302722","https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":1.2743,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.87659887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3152","last_page":"3161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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":0.9998999834060669,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9987999796867371,"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":0.9968000054359436,"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":0.77192223072052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.743182897567749},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6908854246139526},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6393678188323975},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.581889271736145},{"id":"https://openalex.org/keywords/photometric-stereo","display_name":"Photometric stereo","score":0.5567782521247864},{"id":"https://openalex.org/keywords/albedo","display_name":"Albedo (alchemy)","score":0.5200283527374268},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5134769082069397},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5039820075035095},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3374670147895813},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20021843910217285}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.77192223072052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.743182897567749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6908854246139526},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6393678188323975},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.581889271736145},{"id":"https://openalex.org/C44365914","wikidata":"https://www.wikidata.org/wiki/Q17120636","display_name":"Photometric stereo","level":3,"score":0.5567782521247864},{"id":"https://openalex.org/C195886398","wikidata":"https://www.wikidata.org/wiki/Q2110050","display_name":"Albedo (alchemy)","level":3,"score":0.5200283527374268},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5134769082069397},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5039820075035095},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3374670147895813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20021843910217285},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C52119013","wikidata":"https://www.wikidata.org/wiki/Q50637","display_name":"Art history","level":1,"score":0.0},{"id":"https://openalex.org/C554144382","wikidata":"https://www.wikidata.org/wiki/Q213156","display_name":"Performance art","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2017.340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W2581345","https://openalex.org/W39428922","https://openalex.org/W1576579612","https://openalex.org/W1892590658","https://openalex.org/W1903480611","https://openalex.org/W1941928608","https://openalex.org/W1975636777","https://openalex.org/W1979449660","https://openalex.org/W1985613629","https://openalex.org/W1987648924","https://openalex.org/W1994184495","https://openalex.org/W2020733757","https://openalex.org/W2026672030","https://openalex.org/W2027560260","https://openalex.org/W2030300879","https://openalex.org/W2035683503","https://openalex.org/W2055537778","https://openalex.org/W2072243466","https://openalex.org/W2080794127","https://openalex.org/W2082253268","https://openalex.org/W2083779601","https://openalex.org/W2087257250","https://openalex.org/W2089079585","https://openalex.org/W2101856619","https://openalex.org/W2101872283","https://openalex.org/W2104349977","https://openalex.org/W2105649179","https://openalex.org/W2110567636","https://openalex.org/W2112417771","https://openalex.org/W2113507517","https://openalex.org/W2116919352","https://openalex.org/W2117035055","https://openalex.org/W2121253532","https://openalex.org/W2124351162","https://openalex.org/W2130840066","https://openalex.org/W2131747574","https://openalex.org/W2133661850","https://openalex.org/W2138306472","https://openalex.org/W2138334472","https://openalex.org/W2153388956","https://openalex.org/W2164847484","https://openalex.org/W2220470871","https://openalex.org/W2246825111","https://openalex.org/W2288223183","https://openalex.org/W3186925805","https://openalex.org/W6600105807","https://openalex.org/W6601593943","https://openalex.org/W6664224851","https://openalex.org/W6679674316","https://openalex.org/W6799437036","https://openalex.org/W6836399945"],"related_works":["https://openalex.org/W2071501285","https://openalex.org/W1904220063","https://openalex.org/W2118082161","https://openalex.org/W4210268023","https://openalex.org/W2122468143","https://openalex.org/W2068149630","https://openalex.org/W2042906516","https://openalex.org/W2115840043","https://openalex.org/W2182270966","https://openalex.org/W1590955951"],"abstract_inverted_index":{"In":[0,100],"this":[1],"paper":[2],"we":[3,44,102],"present":[4,103],"a":[5,61,83],"novel":[6],"approach":[7],"for":[8],"depth":[9],"map":[10],"enhancement":[11],"from":[12,60],"an":[13,104],"RGB-D":[14],"video":[15],"sequence.":[16,29],"The":[17,67],"basic":[18],"idea":[19],"is":[20,71],"to":[21,72,107,130],"exploit":[22],"the":[23,27,46,76,109],"photometric":[24,58],"information":[25],"in":[26,95],"color":[28],"Instead":[30],"of":[31,97],"making":[32],"any":[33,116],"assumption":[34],"about":[35],"surface":[36,110,137],"albedo":[37,113],"or":[38],"controlled":[39],"object":[40,52,63],"motion":[41],"and":[42,112,127,140],"lighting,":[43],"use":[45],"lighting":[47,84,98],"variations":[48],"introduced":[49],"by":[50],"casual":[51],"movement.":[53],"We":[54,80,119],"are":[55],"effectively":[56],"calculating":[57],"stereo":[59],"moving":[62],"under":[64],"natural":[65],"illuminations.":[66],"key":[68],"technical":[69],"challenge":[70],"establish":[73],"correspondences":[74],"over":[75],"entire":[77],"image":[78],"set.":[79],"therefore":[81],"develop":[82],"insensitive":[85],"robust":[86],"pixel":[87],"matching":[88],"technique":[89],"that":[90],"out-performs":[91],"optical":[92],"flow":[93],"method":[94,123],"presence":[96],"variations.":[99],"addition":[101],"expectation-maximization":[105],"framework":[106],"recover":[108],"normal":[111],"simultaneously,":[114],"without":[115],"regularization":[117],"term.":[118],"have":[120],"validated":[121],"our":[122],"on":[124,135],"both":[125,136],"synthetic":[126],"real":[128],"datasets":[129],"show":[131],"its":[132],"superior":[133],"performance":[134],"details":[138],"recovery":[139],"intrinsic":[141],"decomposition.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
