{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:17:30Z","timestamp":1780355850717,"version":"3.54.1"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/tpami.2023.3312123","type":"journal-article","created":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T17:47:12Z","timestamp":1693936032000},"page":"14248-14265","source":"Crossref","is-referenced-by-count":29,"title":["Comprehensive Vulnerability Evaluation of Face Recognition Systems to Template Inversion Attacks via 3D Face Reconstruction"],"prefix":"10.1109","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8199-0098","authenticated-orcid":false,"given":"Hatef Otroshi","family":"Shahreza","sequence":"first","affiliation":[{"name":"Biometrics Security and Privacy Group, Idiap Research Institute, Martigny, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2497-9140","authenticated-orcid":false,"given":"S\u00e9bastien","family":"Marcel","sequence":"additional","affiliation":[{"name":"Biometrics Security and Privacy Group, Idiap Research Institute, Martigny, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00574"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00395"},{"key":"ref15","first-page":"13 503","article-title":"StyleSDF: High-resolution 3D-consistent image and geometry generation","author":"or-el","year":"2022","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01129"},{"key":"ref53","article-title":"Information Technology &#x2013; Biometric Presentation Attack Detection &#x2013; Part 3: Testing and Reporting, ISO\/IEC 30107&#x2013;3:2017(E), International Organization for Standardization International Standard","year":"2017"},{"key":"ref52","first-page":"1","article-title":"Continuously reproducing toolchains in pattern recognition and machine learning experiments","author":"anjos","year":"2017","journal-title":"Proc ICML Reproducibility Mach Learn Workshop"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19784-0_20"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00629"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00281"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01788"},{"key":"ref16","first-page":"1","article-title":"StyleNeRF: A style-based 3D aware generator for high-resolution image synthesis","author":"gu","year":"2022","journal-title":"Proc 10th Int Conf Learn Representations"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3550454.3555506"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01565"},{"key":"ref51","article-title":"Labeled faces in the wild: A database for studying face recognition in unconstrained environments","author":"huang","year":"2007"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1049\/iet-bmt.2012.0059"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01352"},{"key":"ref42","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref41","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3478324"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00164"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_6"},{"key":"ref8","first-page":"405","article-title":"NeRF: Representing scenes as neural radiance fields for view synthesis","author":"mildenhall","year":"2020","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"ref9","first-page":"20 154","article-title":"GRAF: Generative radiance fields for 3D-aware image synthesis","author":"schwarz","year":"2020","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2014.2381273"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2015.2437652"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-5288-3"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/2.294849"},{"key":"ref35","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"karras","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref34","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"ref36","first-page":"14 745","article-title":"TransGAN: Two pure transformers can make one strong GAN, and that can scale up","author":"jiang","year":"2021","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref31","first-page":"1","article-title":"Realistic face reconstruction from deep embeddings","author":"vendrow","year":"2021","journal-title":"Proc NeurIPS Workshop Privacy Mach Learn"},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1109\/ICCVW60793.2023.00341","article-title":"Controllable inversion of black-box face-recognition models via diffusion","author":"kansy","year":"2023"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-08-051581-6.50065-9"},{"key":"ref32","article-title":"Reconstruct face from features using GAN generator as a distribution constraint","author":"dong","year":"2022"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2015.2426728"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.08.022"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-7744-1_2"},{"key":"ref38","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","author":"dhariwal","year":"2021","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2827389"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.361"},{"key":"ref26","article-title":"Vec2Face-V2: Unveil human faces from their blackbox features via attention-based network in face recognition","author":"truong","year":"2022"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00617"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00353"},{"key":"ref22","article-title":"Inverting face embeddings with convolutional neural networks","author":"zhmoginov","year":"2016"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00161"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/BIOSIG52210.2021.9548290"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BIOSIG55365.2022.9896963"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3577923.3583645"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10308548\/10239446.pdf?arnumber=10239446","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T14:38:46Z","timestamp":1730039926000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10239446\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":54,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2023.3312123","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}