{"id":"https://openalex.org/W4226058682","doi":"https://doi.org/10.1109/tpami.2023.3319429","title":"Fine Detailed Texture Learning for 3D Meshes With Generative Models","display_name":"Fine Detailed Texture Learning for 3D Meshes With Generative Models","publication_year":2023,"publication_date":"2023-09-26","ids":{"openalex":"https://openalex.org/W4226058682","doi":"https://doi.org/10.1109/tpami.2023.3319429","pmid":"https://pubmed.ncbi.nlm.nih.gov/37751344"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3319429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3319429","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5041525280","display_name":"Ay\u015feg\u00fcl D\u00fcndar","orcid":"https://orcid.org/0000-0003-2014-6325"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Aysegul Dundar","raw_affiliation_strings":["Department of Computer Science, Bilkent University, Ankara, Turkey"],"raw_orcid":"https://orcid.org/0000-0003-2014-6325","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Bilkent University, Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Gao","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025713692","display_name":"Andrew Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Tao","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066242985","display_name":"Bryan Catanzaro","orcid":"https://orcid.org/0000-0003-0034-7728"},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Catanzaro","raw_affiliation_strings":["NVIDIA, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210127875"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00428348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"12","first_page":"14563","last_page":"14574"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8661999702453613,"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":0.8661999702453613,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.11180000007152557,"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/T11448","display_name":"Face recognition and analysis","score":0.004900000058114529,"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-science","display_name":"Computer science","score":0.7606570720672607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6648521423339844},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6537216901779175},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6430938243865967},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.5837860107421875},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.563348650932312},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49825167655944824},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.47177743911743164},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.4661228656768799},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4165520966053009},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.2935532331466675}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7606570720672607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6648521423339844},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6537216901779175},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6430938243865967},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.5837860107421875},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.563348650932312},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49825167655944824},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.47177743911743164},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.4661228656768799},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4165520966053009},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2935532331466675},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3319429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3319429","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37751344","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37751344","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W183071939","https://openalex.org/W309515887","https://openalex.org/W1991264156","https://openalex.org/W2128942651","https://openalex.org/W2194775991","https://openalex.org/W2342277278","https://openalex.org/W2471962767","https://openalex.org/W2519683295","https://openalex.org/W2793768642","https://openalex.org/W2912459656","https://openalex.org/W2933283236","https://openalex.org/W2962770929","https://openalex.org/W2962912205","https://openalex.org/W2962974533","https://openalex.org/W2963150697","https://openalex.org/W2963527086","https://openalex.org/W2963739349","https://openalex.org/W2963850211","https://openalex.org/W2982697283","https://openalex.org/W2985068832","https://openalex.org/W2990173985","https://openalex.org/W2991332406","https://openalex.org/W3014859719","https://openalex.org/W3034515601","https://openalex.org/W3034968345","https://openalex.org/W3035148830","https://openalex.org/W3035413889","https://openalex.org/W3035520874","https://openalex.org/W3035574324","https://openalex.org/W3107127767","https://openalex.org/W3107541696","https://openalex.org/W3110135946","https://openalex.org/W3173531806","https://openalex.org/W3176179930","https://openalex.org/W3177583232","https://openalex.org/W3197074992","https://openalex.org/W4214701208","https://openalex.org/W4312453532","https://openalex.org/W6600609147","https://openalex.org/W6639102338","https://openalex.org/W6734074887","https://openalex.org/W6739901393","https://openalex.org/W6752378368","https://openalex.org/W6765978013","https://openalex.org/W6769148693","https://openalex.org/W6772766308","https://openalex.org/W6774631009","https://openalex.org/W6779574250","https://openalex.org/W6781568228","https://openalex.org/W6784133018","https://openalex.org/W6785987360","https://openalex.org/W6786190520","https://openalex.org/W6797770180","https://openalex.org/W6802668286"],"related_works":["https://openalex.org/W206613","https://openalex.org/W12940665","https://openalex.org/W10927761","https://openalex.org/W10828093","https://openalex.org/W5239314","https://openalex.org/W1014668","https://openalex.org/W16531093","https://openalex.org/W13241864","https://openalex.org/W5899557","https://openalex.org/W10405577"],"abstract_inverted_index":{"This":[0],"paper":[1,66],"presents":[2],"a":[3,58,112],"method":[4,147],"to":[5,119,154],"achieve":[6,123],"fine":[7],"detailed":[8],"texture":[9,56,105],"learning":[10,43,54,71],"for":[11],"3D":[12,150],"models":[13,152],"that":[14,92,145],"are":[15,67],"reconstructed":[16],"from":[17,129],"both":[18],"multi-view":[19,127],"and":[20,31,141],"single-view":[21,136],"images.":[22],"The":[23,62],"framework":[24],"is":[25,32],"posed":[26],"as":[27,132,134],"an":[28,89],"adaptation":[29],"problem":[30],"done":[33],"progressively":[34],"where":[35,73],"in":[36,47,68],"the":[37,48,55,65,69,80,95,117,120,155],"first":[38],"stage,":[39,50],"we":[40,51,74,87,107],"focus":[41,52],"on":[42,53,94,126,135],"accurate":[44],"geometry,":[45],"whereas":[46],"second":[49],"with":[57,111],"generative":[59,70],"adversarial":[60],"network.":[61],"contributions":[63],"of":[64,98],"pipeline":[72],"propose":[75,88],"two":[76],"improvements.":[77],"First,":[78],"since":[79,101],"learned":[81],"textures":[82],"should":[83],"be":[84],"spatially":[85],"aligned,":[86],"attention":[90],"mechanism":[91],"relies":[93],"learnable":[96,113],"positions":[97],"pixels.":[99],"Second,":[100],"discriminator":[102],"receives":[103],"aligned":[104],"maps,":[106],"augment":[108],"its":[109],"input":[110],"embedding":[114],"which":[115],"improves":[116],"feedback":[118],"generator.":[121],"We":[122,143],"significant":[124],"improvements":[125],"sequences":[128],"Tripod":[130],"dataset":[131],"well":[133],"image":[137],"datasets,":[138],"Pascal":[139],"3D+":[140],"CUB.":[142],"demonstrate":[144],"our":[146],"achieves":[148],"superior":[149],"textured":[151],"compared":[153],"previous":[156],"works.":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-05-05T00:00:00"}
