{"id":"https://openalex.org/W6929833732","doi":"https://doi.org/10.5075/epfl-thesis-7974","title":"Learning to Represent and Reconstruct 3D Deformable Objects","display_name":"Learning to Represent and Reconstruct 3D Deformable Objects","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6929833732","doi":"https://doi.org/10.5075/epfl-thesis-7974"},"language":"en","primary_location":{"id":"pmh:oai:infoscience.epfl.ch:292534","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/186031","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":null,"raw_type":"doctoral thesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/186031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bednar\u00edk, Jan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bednar\u00edk, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9376000165939331,"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":0.9376000165939331,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.01730000041425228,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.004800000227987766,"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/focus","display_name":"Focus (optics)","score":0.6617000102996826},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5440000295639038},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5400000214576721},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5203999876976013},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4674000144004822},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4596000015735626},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.44350001215934753},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.33550000190734863},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3158999979496002}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7488999962806702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7426999807357788},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6931999921798706},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6617000102996826},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5400000214576721},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5203999876976013},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.28859999775886536},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28369998931884766},{"id":"https://openalex.org/C2776863239","wikidata":"https://www.wikidata.org/wiki/Q7936601","display_name":"Visual hull","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C112604564","wikidata":"https://www.wikidata.org/wiki/Q7489226","display_name":"Shape analysis (program analysis)","level":3,"score":0.2515999972820282}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:infoscience.epfl.ch:292534","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/186031","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":null,"raw_type":"doctoral thesis"},{"id":"doi:10.5075/epfl-thesis-7974","is_oa":true,"landing_page_url":"https://doi.org/10.5075/epfl-thesis-7974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dissertation"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:292534","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/186031","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"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":null,"raw_type":"doctoral thesis"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Representing":[0],"and":[1,40,172,194,199,213,219,234,238,273,324,402,453,489],"reconstructing":[2],"3D":[3,169,467],"deformable":[4,192,435],"shapes":[5,22,65,193],"are":[6,23],"two":[7],"tightly":[8],"linked":[9],"problems":[10],"that":[11,145,338,381,415,463],"have":[12],"long":[13],"been":[14],"studied":[15],"within":[16],"the":[17,27,64,69,74,101,110,127,136,165,180,205,229,249,255,266,279,283,297,301,312,316,328,334,366,371,399,410,458,470],"computer":[18,56,130],"vision":[19,57,131],"field.":[20],"Deformable":[21],"truly":[24],"ubiquitous":[25],"in":[26,68,100,160,290,349,474],"real":[28],"world,":[29],"whether":[30],"be":[31,60,95,122,187],"it":[32,286,293,339,404,492],"specific":[33],"object":[34,348],"classes":[35],"such":[36,46,358,377],"as":[37,47,207],"humans,":[38],"garments":[39],"animals":[41],"or":[42],"more":[43],"abstract":[44],"ones":[45],"generic":[48,146],"materials":[49],"deforming":[50,347,487],"under":[51],"an":[52,96,208],"external":[53],"force.":[54],"Practical":[55],"algorithms":[58],"must":[59],"able":[61],"to":[62,72,86,94,121,186,296,356,405,457],"understand":[63],"of":[66,77,104,138,167,178,210,248,268,282,300,345,398,432,469,485],"objects":[67,472,488],"observed":[70,459],"scenes":[71],"unlock":[73],"wide":[75],"spectrum":[76],"much":[78],"sought":[79],"after":[80],"applications":[81],"ranging":[82],"from":[83,153],"virtual":[84],"try-on":[85],"automated":[87],"surgeries.":[88],"Automatic":[89],"shape":[90,170,270,436],"reconstruction":[91,261,359,476],"is":[92,287,294,355],"known":[93],"ill-posed":[97],"problem,":[98],"especially":[99,188],"common":[102],"scenario":[103],"a":[105,320,342,346,350,429,440,447,450,454,480],"single":[106],"image":[107],"input.":[108],"Therefore,":[109],"modern":[111],"approaches":[112],"rely":[113],"on":[114,176,244,275,370,421],"deep":[115,147],"learning":[116,148,442],"paradigm":[117],"which":[118,183,195,314,444],"has":[119],"proven":[120],"extremely":[123],"effective":[124],"even":[125],"for":[126,190,216,493],"severely":[128],"under-constrained":[129],"problems.":[132],"We,":[133],"too,":[134],"exploit":[135],"success":[137],"data-driven":[139],"approaches,":[140],"however,":[141],"we":[142,173,196,239,305,332,379,395,426,490],"also":[143],"show":[144,414,462],"models":[149,204],"can":[150],"greatly":[151],"benefit":[152],"being":[154],"combined":[155],"with":[156],"explicit":[157],"knowledge":[158],"originating":[159],"computational":[161],"geometry.":[162],"We":[163,223,263,438,461,478],"analyze":[164],"use":[166,397],"various":[168],"representations":[171,468],"distinctly":[174],"focus":[175,274],"one":[177],"them,":[179],"atlas-based":[181,202,269,335],"representation,":[182],"turns":[184],"out":[185],"suitable":[189],"modeling":[191],"further":[197],"improve":[198],"extend.":[200],"The":[201,353,412],"representation":[203,271,336],"surfaces":[206],"ensemble":[209],"continuous":[211],"functions":[212,308],"thus":[214,325],"allows":[215],"arbitrary":[217],"resolution":[218],"analytical":[220],"surface":[221,318,362,384],"analysis.":[222],"identify":[224],"its":[225,388],"major":[226],"shortcomings,":[227],"namely":[228],"patch":[230,232],"collapse,":[231],"overlap":[233],"strong":[235],"mapping":[236],"distortions,":[237],"propose":[240,439],"novel":[241],"regularizers":[242],"based":[243],"analytically":[245],"computed":[246],"properties":[247],"reconstructed":[250,302],"surfaces.":[251,303],"Our":[252],"approach":[253,443],"counteracts":[254],"aforementioned":[256],"drawbacks":[257],"while":[258],"yielding":[259],"higher":[260,475],"accuracy.":[262],"dive":[264],"into":[265,428],"problematics":[267],"deeper":[272],"another":[276],"design":[277,306],"flaw,":[278],"global":[280],"inconsistency":[281],"mappings.":[284],"While":[285],"not":[288],"reflected":[289],"quantitative":[291],"metrics,":[292],"detrimental":[295],"visual":[298,329],"quality":[299],"Specifically,":[304],"loss":[307],"encouraging":[309],"intercommunication":[310],"among":[311],"mappings":[313],"pushes":[315],"resulting":[317],"towards":[319],"C1":[321],"smooth":[322],"function":[323],"dramatically":[326],"improves":[327],"quality.":[330,477],"Furthermore,":[331],"adapt":[333],"so":[337],"could":[340],"model":[341],"full":[343],"sequence":[344],"temporally-consistent":[351],"way.":[352],"goal":[354],"produce":[357],"where":[360],"each":[361,383],"point":[363,369,385],"always":[364],"represents":[365],"same":[367,471],"semantic":[368,389],"target":[372],"GT":[373],"surface.":[374,460],"To":[375],"achieve":[376],"behavior,":[378],"note":[380],"if":[382],"deforms":[386],"close-to-isometrically,":[387],"location":[390],"likely":[391],"remains":[392],"unchanged.":[393],"Practically,":[394],"make":[396],"Riemannian":[400],"metric,":[401],"force":[403],"remain":[406],"point-wise":[407],"constant":[408],"throughout":[409],"sequence.":[411],"experiments":[413],"our":[416],"method":[417],"yields":[418],"SotA":[419],"results":[420,473],"correspondence":[422],"estimation":[423],"task.":[424],"Finally,":[425],"look":[427],"particular":[430],"problem":[431],"monocular":[433],"texture-less":[434,486],"reconstruction.":[437],"multi-task":[441],"jointly":[445],"produces":[446],"normal":[448],"map,":[449],"depth":[451],"map":[452],"mesh":[455],"corresponding":[456],"producing":[464],"multiple":[465],"different":[466],"acquire":[479],"large":[481],"real-world":[482],"annotated":[483],"dataset":[484],"release":[491],"public":[494],"use.":[495]},"counts_by_year":[],"updated_date":"2026-07-23T05:56:39.545243","created_date":"2025-10-10T00:00:00"}
