{"id":"https://openalex.org/W7160300758","doi":"https://doi.org/10.1109/wacv61042.2026.00025","title":"End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards","display_name":"End-to-End Fine-Tuning of 3D Texture Generation using Differentiable Rewards","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160300758","doi":"https://doi.org/10.1109/wacv61042.2026.00025"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","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/A5056349766","display_name":"AmirHossein Zamani","orcid":"https://orcid.org/0009-0007-0866-5700"},"institutions":[{"id":"https://openalex.org/I4210164802","display_name":"Mila - Quebec Artificial Intelligence Institute","ror":"https://ror.org/05c22rx21","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210164802"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"AmirHossein Zamani","raw_affiliation_strings":["Mila – Quebec AI Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mila – Quebec AI Institute","institution_ids":["https://openalex.org/I4210164802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112862480","display_name":"Tianhao Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tianhao Xie","raw_affiliation_strings":["Concordia University,Montreal,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University,Montreal,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023864111","display_name":"Amir G. Aghdam","orcid":"https://orcid.org/0000-0001-5180-0508"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Amir G. Aghdam","raw_affiliation_strings":["Concordia University,Montreal,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University,Montreal,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135372445","display_name":"Tiberiu Popa","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tiberiu Popa","raw_affiliation_strings":["Concordia University,Montreal,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University,Montreal,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126106771","display_name":"Eugene Belilovsky","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164802","display_name":"Mila - Quebec Artificial Intelligence Institute","ror":"https://ror.org/05c22rx21","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210164802"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Eugene Belilovsky","raw_affiliation_strings":["Mila – Quebec AI Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mila – Quebec AI Institute","institution_ids":["https://openalex.org/I4210164802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.70673294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.42239999771118164,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.42239999771118164,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.28870001435279846,"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":0.17589999735355377,"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/texture","display_name":"Texture (cosmology)","score":0.4056999981403351},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.33410000801086426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3122999966144562},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2802000045776367},{"id":"https://openalex.org/keywords/texture-synthesis","display_name":"Texture synthesis","score":0.27630001306533813}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4887000024318695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45509999990463257},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4056999981403351},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3628000020980835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3553999960422516},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.27630001306533813},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26829999685287476},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321588","display_name":"Concordia University","ror":"https://ror.org/0420zvk78"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2128728535","https://openalex.org/W2245625259","https://openalex.org/W2294798173","https://openalex.org/W2990173985","https://openalex.org/W3106672182","https://openalex.org/W3198675127","https://openalex.org/W4200150166","https://openalex.org/W4312933868","https://openalex.org/W4385271281","https://openalex.org/W4385537219","https://openalex.org/W4386065887","https://openalex.org/W4386075992","https://openalex.org/W4390871736","https://openalex.org/W4390873054","https://openalex.org/W4390873135","https://openalex.org/W4390874002","https://openalex.org/W4402753917","https://openalex.org/W4403792041","https://openalex.org/W4404893159","https://openalex.org/W7133185348","https://openalex.org/W7133195264","https://openalex.org/W7133208264","https://openalex.org/W7133208539","https://openalex.org/W7133211372","https://openalex.org/W7133217041","https://openalex.org/W7133250524","https://openalex.org/W7160011528"],"related_works":[],"abstract_inverted_index":{"While":[0],"recent":[1],"3D":[2,27,52,57,83,108,138],"generative":[3,43],"models":[4],"can":[5],"produce":[6],"high-quality":[7,137],"texture":[8,28,84],"images,":[9],"they":[10],"often":[11],"fail":[12],"to":[13,40],"capture":[14],"human":[15,73],"preferences":[16],"or":[17],"meet":[18],"task-specific":[19],"requirements.":[20],"Moreover,":[21],"a":[22,129],"core":[23],"challenge":[24],"in":[25],"the":[26,51,55,82,98,107],"generation":[29],"domain":[30],"is":[31,166],"that":[32,71,105,155],"most":[33],"existing":[34,161],"approaches":[35],"rely":[36],"on":[37],"repeated":[38],"calls":[39],"2D":[41],"text-to-image":[42],"models,":[44],"which":[45,127],"lack":[46],"an":[47,66],"inherent":[48],"understanding":[49],"of":[50,54,97],"structure":[53,110],"input":[56],"mesh":[58],"object.":[59],"To":[60,116],"alleviate":[61],"these":[62],"issues,":[63],"we":[64,120,153],"propose":[65],"end-to-end":[67],"differentiable,":[68],"reinforcement-learning-free":[69],"framework":[70],"embeds":[72],"feedback,":[74],"expressed":[75],"as":[76],"differentiable":[77],"reward":[78,125],"functions,":[79,126],"directly":[80],"into":[81],"synthesis":[85],"pipeline.":[86],"By":[87,143],"back-propagating":[88],"preference":[89],"signals":[90],"through":[91],"both":[92],"geometric":[93],"and":[94,111,132,147],"appearance":[95],"modules":[96],"proposed":[99,157],"framework,":[100],"our":[101,156],"method":[102],"generates":[103],"textures":[104],"respect":[106],"geometry":[109],"align":[112],"with":[113],"desired":[114],"criteria.":[115],"demonstrate":[117,154],"its":[118],"versatility,":[119],"introduce":[121],"three":[122],"novel":[123],"geometry-aware":[124],"offer":[128],"more":[130],"controllable":[131],"interpretable":[133],"pathway":[134],"for":[135],"creating":[136],"content":[139],"from":[140],"natural":[141],"language.":[142],"conducting":[144],"qualitative,":[145],"quantitative,":[146],"user-preference":[148],"evaluations":[149],"against":[150],"state-of-the-art":[151],"methods,":[152],"strategy":[158],"consistently":[159],"outperforms":[160],"approaches.":[162],"Our":[163],"implementation":[164],"code":[165],"publicly":[167],"available":[168],"at:":[169],"https://github.com/AHHHZ975/Differentiable-Texture-Learning":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}