{"id":"https://openalex.org/W2113469957","doi":"https://doi.org/10.1109/iccv.2007.4408976","title":"The Joint Manifold Model for Semi-supervised Multi-valued Regression","display_name":"The Joint Manifold Model for Semi-supervised Multi-valued Regression","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2113469957","doi":"https://doi.org/10.1109/iccv.2007.4408976","mag":"2113469957"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2007.4408976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4408976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","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/A5111952908","display_name":"Ramanan Navaratnam","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096386","display_name":"Bridge University","ror":"https://ror.org/00cbm0437","country_code":"SS","type":"education","lineage":["https://openalex.org/I4210096386"]},{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB","SS"],"is_corresponding":true,"raw_author_name":"Ramanan Navaratnam","raw_affiliation_strings":["University of Cambridge, Cambridge, UK","University of Cambridge, Cambridge"],"affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, Cambridge","institution_ids":["https://openalex.org/I4210096386","https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018851970","display_name":"Andrew Fitzgibbon","orcid":"https://orcid.org/0000-0002-9839-660X"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Andrew W. Fitzgibbon","raw_affiliation_strings":["Microsoft Research Cambridge, Cambridge, UK","Microsoft Research, Cambridge, 7 JJ Thomson Ave, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, 7 JJ Thomson Ave, Cambridge, UK","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018207993","display_name":"Roberto Cipolla","orcid":"https://orcid.org/0000-0002-8999-2151"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Roberto Cipolla","raw_affiliation_strings":["University of Cambridge, Cambridge, UK","University of Cambridge, Trumpington St, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, Trumpington St, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111952908"],"corresponding_institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210096386"],"apc_list":null,"apc_paid":null,"fwci":9.5352,"has_fulltext":false,"cited_by_count":101,"citation_normalized_percentile":{"value":0.98306616,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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/T12290","display_name":"Human Motion and Animation","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.555016040802002},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4875730872154236},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46132439374923706},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4502246081829071},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.4101761281490326},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3425842225551605}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.555016040802002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4875730872154236},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46132439374923706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4502246081829071},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.4101761281490326},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3425842225551605},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/iccv.2007.4408976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4408976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.106.4532","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.106.4532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2007-ICCV-manifold-learning.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.568.3764","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.568.3764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www0.cs.ucl.ac.uk/staff/s.prince/Reading/FitzgibbonICCV.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.88.8747","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.88.8747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/~awf/jmm/techreport.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.90.2200","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.2200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/~awf/jmm/iccv07.pdf","raw_type":"text"},{"id":"pmh:oai:generic.eprints.org:344710","is_oa":false,"landing_page_url":"http://publications.eng.cam.ac.uk/344710/","pdf_url":null,"source":{"id":"https://openalex.org/S4406922847","display_name":"Cambridge University Engineering Department Publications Database","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W194200989","https://openalex.org/W1663973292","https://openalex.org/W1900101064","https://openalex.org/W2001141328","https://openalex.org/W2009086942","https://openalex.org/W2051812123","https://openalex.org/W2097412577","https://openalex.org/W2097944344","https://openalex.org/W2099338527","https://openalex.org/W2099768828","https://openalex.org/W2100247253","https://openalex.org/W2103510282","https://openalex.org/W2104156750","https://openalex.org/W2128221272","https://openalex.org/W2131226188","https://openalex.org/W2136111243","https://openalex.org/W2136504847","https://openalex.org/W2137674454","https://openalex.org/W2143002705","https://openalex.org/W2158268505","https://openalex.org/W2158638750","https://openalex.org/W2159498975","https://openalex.org/W2165876389","https://openalex.org/W2947000318","https://openalex.org/W3140968660","https://openalex.org/W6607781037","https://openalex.org/W6629510986","https://openalex.org/W6675622099","https://openalex.org/W6675990044","https://openalex.org/W6679278974","https://openalex.org/W6679317373","https://openalex.org/W6680140577","https://openalex.org/W6680375596","https://openalex.org/W6680658066","https://openalex.org/W6683344514","https://openalex.org/W6684390964"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W2055243143","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2052122378","https://openalex.org/W2544423928","https://openalex.org/W2062023542"],"abstract_inverted_index":{"Many":[0],"computer":[1],"vision":[2],"tasks":[3],"may":[4],"be":[5,147],"expressed":[6],"as":[7,233,235],"the":[8,33,58,72,92,112,116,119,127,133,177,186,213],"problem":[9],"of":[10,60,105,129,215,241],"learning":[11],"a":[12,18,169,180],"mapping":[13,34,178],"between":[14],"image":[15,36,86],"space":[16],"and":[17,141,188,200,208],"parameter":[19,189],"space.":[20],"For":[21],"example,":[22],"in":[23,57,115],"human":[24],"body":[25],"pose":[26],"estimation,":[27],"recent":[28],"research":[29],"has":[30],"directly":[31],"modelled":[32],"from":[35,68,132,179],"features":[37,87],"(":[38,46,62,94],"<b":[39,47,63,76,88,95,137,143],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[40,48,64,77,89,96,138,144],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">z</b>":[41,65,78,90,97,139],")":[42,140],"to":[43,110,149,161,175,185,195],"joint":[44],"angles":[45],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u03b8</b>":[49,145],").":[50],"Fitting":[51],"such":[52],"models":[53],"requires":[54],"training":[55,106],"data":[56,107,217],"form":[59],"labelled":[61,165],"\u03b8)":[66,98],"pairs,":[67],"which":[69,237],"are":[70,108,121,230],"learned":[71],"conditional":[73,93],"densities":[74],"p(":[75,136,142],"\u03b8).":[79],"Inference":[80],"is":[81,99,153,157],"then":[82],"simple:":[83],"given":[84],"test":[85],",":[91],"immediately":[100],"computed.":[101],"However":[102],"large":[103],"amounts":[104],"required":[109],"fit":[111],"models,":[113],"particularly":[114],"case":[117],"where":[118],"spaces":[120],"high":[122],"dimensional.":[123],"We":[124,167],"show":[125],"how":[126,212],"use":[128,168,197,214,240],"unlabelled":[130,163,198,216,242],"data\u2014samples":[131],"marginal":[134],"distributions":[135],")\u2014may":[146],"used":[148],"improve":[150],"fitting.":[151],"This":[152,191],"valuable":[154],"because":[155],"it":[156],"often":[158],"significantly":[159],"easier":[160],"obtain":[162],"than":[164],"samples.":[166],"Gaussian":[170],"process":[171],"latent":[172,182],"variable":[173],"model":[174],"learn":[176],"shared":[181],"low-dimensional":[183],"manifold":[184],"feature":[187],"spaces.":[190],"extends":[192],"existing":[193,220,227],"approaches":[194,228],"(a)":[196],"data,":[199],"(b)":[201],"represent":[202],"one-to-many":[203],"mappings.":[204],"Experiments":[205],"on":[206],"synthetic":[207],"real":[209],"problems":[210],"demonstrate":[211],"improves":[218],"over":[219],"techniques.":[221],"In":[222],"our":[223],"comparisons,":[224],"we":[225],"include":[226],"that":[229],"explicitly":[231],"semi-supervised":[232],"well":[234],"those":[236],"implicitly":[238],"make":[239],"examples.":[243]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":9}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}