{"id":"https://openalex.org/W2000044793","doi":"https://doi.org/10.1109/cvpr.2010.5540155","title":"Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction","display_name":"Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2000044793","doi":"https://doi.org/10.1109/cvpr.2010.5540155","mag":"2000044793"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5540155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society 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/A5049300388","display_name":"Mathieu Salzmann","orcid":"https://orcid.org/0000-0002-8347-8637"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mathieu Salzmann","raw_affiliation_strings":["EECS & ICSI, University of California, Berkeley, USA","EECS & ICSI, UC Berkeley"],"affiliations":[{"raw_affiliation_string":"EECS & ICSI, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS & ICSI, UC Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058557954","display_name":"Raquel Urtasun","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raquel Urtasun","raw_affiliation_strings":["TTI, Chicago, USA","TTI, Chicago"],"affiliations":[{"raw_affiliation_string":"TTI, Chicago, USA","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"TTI, Chicago","institution_ids":["https://openalex.org/I160992636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049300388"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":10.9831,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.98895043,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9984999895095825,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9976999759674072,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9970999956130981,"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/discriminative-model","display_name":"Discriminative model","score":0.9703631401062012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7686862349510193},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6850143671035767},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6797394752502441},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6338778138160706},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5267376899719238},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49767211079597473},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.48528167605400085},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40578675270080566},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32384437322616577},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26775282621383667}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9703631401062012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7686862349510193},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6850143671035767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797394752502441},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6338778138160706},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5267376899719238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49767211079597473},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.48528167605400085},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40578675270080566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32384437322616577},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26775282621383667},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2010.5540155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540155","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.175.4104","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.4104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ttic.edu/urtasun/publications/salzmann_urtasun_cvpr10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1540155273","https://openalex.org/W1543654609","https://openalex.org/W1861517257","https://openalex.org/W2014561430","https://openalex.org/W2097412577","https://openalex.org/W2103025041","https://openalex.org/W2104346056","https://openalex.org/W2108825216","https://openalex.org/W2121717851","https://openalex.org/W2123094226","https://openalex.org/W2128482493","https://openalex.org/W2128638437","https://openalex.org/W2132026986","https://openalex.org/W2136745795","https://openalex.org/W2143116634","https://openalex.org/W2144124341","https://openalex.org/W2152926413","https://openalex.org/W2158268505","https://openalex.org/W2158638750","https://openalex.org/W2158866619","https://openalex.org/W2165350702","https://openalex.org/W2169433763","https://openalex.org/W2334018742","https://openalex.org/W4253295021","https://openalex.org/W6675631895","https://openalex.org/W6675945460","https://openalex.org/W6680269927","https://openalex.org/W6680910205","https://openalex.org/W6684741808"],"related_works":["https://openalex.org/W2987280934","https://openalex.org/W2093104230","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W4386184937","https://openalex.org/W3014948380","https://openalex.org/W2751624083","https://openalex.org/W4241564561"],"abstract_inverted_index":{"Historically":[0],"non-rigid":[1,16],"shape":[2,17],"recovery":[3,18],"and":[4,67,92,101,128],"articulated":[5,98],"pose":[6,42,99],"estimation":[7,43,100],"have":[8,19,27,44],"evolved":[9],"as":[10],"separate":[11],"fields.":[12],"Recent":[13],"methods":[14,75,113,130],"for":[15,41,51,97,123],"focused":[20],"on":[21],"improving":[22],"the":[23,30,52,70,109,124],"algorithmic":[24],"formulation,":[25],"but":[26],"only":[28],"considered":[29],"case":[31],"of":[32,54,108,111,126],"reconstruction":[33],"from":[34,69,89],"point-to-point":[35],"correspondences.":[36],"In":[37,83],"contrast,":[38],"many":[39],"techniques":[40,61],"followed":[45],"a":[46,94,132],"discriminative":[47,74,112,129],"approach,":[48],"which":[49],"allows":[50,122],"use":[53],"more":[55],"general":[56],"image":[57],"cues.":[58],"However,":[59],"these":[60],"typically":[62],"require":[63],"large":[64],"training":[65],"sets":[66],"suffer":[68],"fact":[71],"that":[72],"standard":[73],"do":[76],"not":[77],"enforce":[78],"constraints":[79],"between":[80],"output":[81],"dimensions.":[82],"this":[84],"paper,":[85],"we":[86],"combine":[87],"ideas":[88],"both":[90],"domains":[91],"propose":[93],"unified":[95],"framework":[96],"3D":[102],"surface":[103],"reconstruction.":[104],"We":[105],"address":[106],"some":[107],"issues":[110],"by":[114],"explicitly":[115],"constraining":[116],"their":[117],"prediction.":[118],"Furthermore,":[119],"our":[120],"formulation":[121],"combination":[125],"generative":[127],"into":[131],"single,":[133],"common":[134],"framework.":[135]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}