{"id":"https://openalex.org/W3035523051","doi":"https://doi.org/10.1109/cvpr42600.2020.00008","title":"Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild","display_name":"Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3035523051","doi":"https://doi.org/10.1109/cvpr42600.2020.00008","mag":"3035523051"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr42600.2020.00008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5032886186","display_name":"Shangzhe Wu","orcid":"https://orcid.org/0000-0003-1011-5963"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Shangzhe Wu","raw_affiliation_strings":["Visual Geometry Group, University of Oxford"],"affiliations":[{"raw_affiliation_string":"Visual Geometry Group, University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083153177","display_name":"Christian Rupprecht","orcid":"https://orcid.org/0000-0003-3994-8045"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christian Rupprecht","raw_affiliation_strings":["Visual Geometry Group, University of Oxford"],"affiliations":[{"raw_affiliation_string":"Visual Geometry Group, University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060511349","display_name":"Andrea Vedaldi","orcid":"https://orcid.org/0000-0003-1374-2858"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andrea Vedaldi","raw_affiliation_strings":["Visual Geometry Group, University of Oxford"],"affiliations":[{"raw_affiliation_string":"Visual Geometry Group, University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032886186"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":18.2553,"has_fulltext":false,"cited_by_count":240,"citation_normalized_percentile":{"value":0.99522546,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9965000152587891,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9959999918937683,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8038244247436523},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7583900690078735},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7388201355934143},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7275673151016235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6677437424659729},{"id":"https://openalex.org/keywords/symmetry","display_name":"Symmetry (geometry)","score":0.6196005344390869},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.574546754360199},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.42955392599105835},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3439401388168335},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.28333327174186707},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2733108401298523},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.14017412066459656}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8038244247436523},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7583900690078735},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7388201355934143},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7275673151016235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6677437424659729},{"id":"https://openalex.org/C2779886137","wikidata":"https://www.wikidata.org/wiki/Q21030012","display_name":"Symmetry (geometry)","level":2,"score":0.6196005344390869},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.574546754360199},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.42955392599105835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3439401388168335},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28333327174186707},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2733108401298523},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.14017412066459656},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr42600.2020.00008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":101,"referenced_works":["https://openalex.org/W19301072","https://openalex.org/W97083571","https://openalex.org/W183071939","https://openalex.org/W1520997877","https://openalex.org/W1567532702","https://openalex.org/W1686810756","https://openalex.org/W1834627138","https://openalex.org/W1967554269","https://openalex.org/W1973016074","https://openalex.org/W1977295328","https://openalex.org/W2013599012","https://openalex.org/W2017814585","https://openalex.org/W2051297709","https://openalex.org/W2067164770","https://openalex.org/W2083880226","https://openalex.org/W2097307110","https://openalex.org/W2107037917","https://openalex.org/W2118304946","https://openalex.org/W2124600577","https://openalex.org/W2147334734","https://openalex.org/W2171740948","https://openalex.org/W2190691619","https://openalex.org/W2321727850","https://openalex.org/W2520707372","https://openalex.org/W2542323081","https://openalex.org/W2546066744","https://openalex.org/W2561074213","https://openalex.org/W2582734987","https://openalex.org/W2600383743","https://openalex.org/W2604672468","https://openalex.org/W2609883120","https://openalex.org/W2770096058","https://openalex.org/W2784996692","https://openalex.org/W2785325870","https://openalex.org/W2795260501","https://openalex.org/W2807725536","https://openalex.org/W2812468425","https://openalex.org/W2883221003","https://openalex.org/W2889582485","https://openalex.org/W2889980536","https://openalex.org/W2903206492","https://openalex.org/W2912459656","https://openalex.org/W2933283236","https://openalex.org/W2945729334","https://openalex.org/W2949671016","https://openalex.org/W2951234442","https://openalex.org/W2952069407","https://openalex.org/W2952610664","https://openalex.org/W2962760512","https://openalex.org/W2962835968","https://openalex.org/W2962946389","https://openalex.org/W2963022858","https://openalex.org/W2963409406","https://openalex.org/W2963527086","https://openalex.org/W2963590054","https://openalex.org/W2963654727","https://openalex.org/W2963823554","https://openalex.org/W2963850211","https://openalex.org/W2963958774","https://openalex.org/W2963995996","https://openalex.org/W2964020152","https://openalex.org/W2964053173","https://openalex.org/W2964094607","https://openalex.org/W2964472976","https://openalex.org/W2968940310","https://openalex.org/W2969485315","https://openalex.org/W2970086547","https://openalex.org/W2973948937","https://openalex.org/W2974067445","https://openalex.org/W2978506573","https://openalex.org/W2981081013","https://openalex.org/W2990173985","https://openalex.org/W3000817459","https://openalex.org/W3004414671","https://openalex.org/W3101531717","https://openalex.org/W3103596843","https://openalex.org/W4255438484","https://openalex.org/W4308831279","https://openalex.org/W4319068731","https://openalex.org/W4394671432","https://openalex.org/W6607472237","https://openalex.org/W6630744482","https://openalex.org/W6637373629","https://openalex.org/W6678355778","https://openalex.org/W6681942348","https://openalex.org/W6685261749","https://openalex.org/W6729001083","https://openalex.org/W6735443497","https://openalex.org/W6735920323","https://openalex.org/W6746200750","https://openalex.org/W6747899497","https://openalex.org/W6748208425","https://openalex.org/W6748955722","https://openalex.org/W6750172629","https://openalex.org/W6752936729","https://openalex.org/W6753219919","https://openalex.org/W6754172994","https://openalex.org/W6754438650","https://openalex.org/W6756444276","https://openalex.org/W6756768591","https://openalex.org/W6765978013"],"related_works":["https://openalex.org/W4287995534","https://openalex.org/W2998168123","https://openalex.org/W3133754756","https://openalex.org/W2897995864","https://openalex.org/W2292254049","https://openalex.org/W2975200075","https://openalex.org/W2007544051","https://openalex.org/W1837097281","https://openalex.org/W1966410754","https://openalex.org/W2363840281"],"abstract_inverted_index":{"We":[0,59],"propose":[1],"a":[2,56,96,136],"method":[3,18,114,149],"to":[4,37,67,81,147],"learn":[5],"3D":[6,120],"deformable":[7],"object":[8,49,71],"categories":[9,50],"from":[10,129],"raw":[11],"single-view":[12,130],"images,":[13,131],"without":[14,41,132],"external":[15],"supervision.":[16],"The":[17],"is":[19,77],"based":[20],"on":[21],"an":[22],"autoencoder":[23],"that":[24,47,61,87,112,150],"factors":[25],"each":[26],"input":[27],"image":[28,158],"into":[29],"depth,":[30],"albedo,":[31],"viewpoint":[32],"and":[33,127],"illumination.":[34],"In":[35],"order":[36],"disentangle":[38],"these":[39],"components":[40,105],"supervision,":[42],"we":[43,84,142],"use":[44],"the":[45,69,75,103,107,119,154],"fact":[46],"many":[48],"have,":[51],"at":[52,153],"least":[53],"in":[54],"principle,":[55],"symmetric":[57,79,93],"structure.":[58],"show":[60,111],"reasoning":[62],"about":[63],"illumination":[64],"allows":[65],"us":[66],"exploit":[68],"underlying":[70],"symmetry":[72,97],"even":[73],"if":[74],"appearance":[76],"not":[78,91],"due":[80],"shading.":[82],"Furthermore,":[83],"model":[85],"objects":[86],"are":[88],"probably,":[89],"but":[90],"certainly,":[92],"by":[94],"predicting":[95],"probability":[98],"map,":[99],"learned":[100],"end-to-end":[101],"with":[102],"other":[104],"of":[106,122,156],"model.":[108,139],"Our":[109],"experiments":[110],"this":[113],"can":[115],"recover":[116],"very":[117],"accurately":[118],"shape":[121,138],"human":[123],"faces,":[124],"cat":[125],"faces":[126],"cars":[128],"any":[133],"supervision":[134,152],"or":[135],"prior":[137],"On":[140],"benchmarks,":[141],"demonstrate":[143],"superior":[144],"accuracy":[145],"compared":[146],"another":[148],"uses":[151],"level":[155],"2D":[157],"correspondences.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":52},{"year":2022,"cited_by_count":45},{"year":2021,"cited_by_count":73},{"year":2020,"cited_by_count":16}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
