{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:53:29Z","timestamp":1769907209780,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072114, U20A20178,U1936214 and U20B2051"],"award-info":[{"award-number":["62072114, U20A20178,U1936214 and U20B2051"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3503161.3548110","type":"proceedings-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T15:43:12Z","timestamp":1665416592000},"page":"1465-1473","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["On Generating Identifiable Virtual Faces"],"prefix":"10.1145","author":[{"given":"Zhuowen","family":"Yuan","sequence":"first","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Zhengxin","family":"You","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Sheng","family":"Li","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Zhenxing","family":"Qian","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Xinpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Alex","family":"Kot","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2022,10,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447648"},{"key":"e_1_3_2_1_2_1","unstructured":"Martin Arjovsky Soumith Chintala and L\u00e9on Bottou. 2017. Wasserstein GAN. arXiv:1701.07875 [stat.ML]  Martin Arjovsky Soumith Chintala and L\u00e9on Bottou. 2017. Wasserstein GAN. arXiv:1701.07875 [stat.ML]"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00020"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"e_1_3_2_1_5_1","volume-title":"Generative adversarial nets. Advances in neural information processing systems 27","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow , Jean Pouget-Abadie , Mehdi Mirza , Bing Xu , David Warde-Farley , Sherjil Ozair , Aaron Courville , and Yoshua Bengio . 2014. Generative adversarial nets. Advances in neural information processing systems 27 ( 2014 ). Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. Advances in neural information processing systems 27 (2014)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_43"},{"key":"e_1_3_2_1_7_1","volume-title":"MegaPixels: origins, ethics, and privacy implications of publicly available face recognition image datasets. Megapixels","author":"Harvey Adam","year":"2019","unstructured":"Adam Harvey and Jules LaPlace . 2019. MegaPixels: origins, ethics, and privacy implications of publicly available face recognition image datasets. Megapixels ( 2019 ). Adam Harvey and Jules LaPlace. 2019. MegaPixels: origins, ethics, and privacy implications of publicly available face recognition image datasets. Megapixels (2019)."},{"key":"e_1_3_2_1_8_1","unstructured":"Martin Heusel Hubert Ramsauer Thomas Unterthiner Bernhard Nessler and Sepp Hochreiter. 2018. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. arXiv:1706.08500 [cs.LG]  Martin Heusel Hubert Ramsauer Thomas Unterthiner Bernhard Nessler and Sepp Hochreiter. 2018. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. arXiv:1706.08500 [cs.LG]"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1515\/popets-2016-0047"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.167"},{"key":"e_1_3_2_1_12_1","unstructured":"Tero Karras Timo Aila Samuli Laine and Jaakko Lehtinen. 2018. Progressive Growing of GANs for Improved Quality Stability and Variation. arXiv:1710.10196 [cs.NE]  Tero Karras Timo Aila Samuli Laine and Jaakko Lehtinen. 2018. Progressive Growing of GANs for Improved Quality Stability and Variation. arXiv:1710.10196 [cs.NE]"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"e_1_3_2_1_14_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2017","unstructured":"Diederik P. Kingma and Jimmy Ba . 2017 . Adam : A Method for Stochastic Optimization . arXiv:1412.6980 [cs.LG] Diederik P. Kingma and Jimmy Ba. 2017. Adam: A Method for Stochastic Optimization. arXiv:1412.6980 [cs.LG]"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475464"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Alexey Kurakin Ian Goodfellow and Samy Bengio. 2017. Adversarial examples in the physical world. arXiv:1607.02533 [cs.CV]  Alexey Kurakin Ian Goodfellow and Samy Bengio. 2017. Adversarial examples in the physical world. arXiv:1607.02533 [cs.CV]","DOI":"10.1201\/9781351251389-8"},{"key":"e_1_3_2_1_17_1","unstructured":"Tao Li and Min Soo Choi. 2021. DeepBlur: A Simple and Effective Method for Natural Image Obfuscation. arXiv:2104.02655 [cs.CV]  Tao Li and Min Soo Choi. 2021. DeepBlur: A Simple and Effective Method for Natural Image Obfuscation. arXiv:2104.02655 [cs.CV]"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00013"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.713"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00549"},{"key":"e_1_3_2_1_23_1","unstructured":"Richard McPherson Reza Shokri and Vitaly Shmatikov. 2016. Defeating Image Obfuscation with Deep Learning. arXiv:1609.00408 [cs.CR]  Richard McPherson Reza Shokri and Vitaly Shmatikov. 2016. Defeating Image Obfuscation with Deep Learning. arXiv:1609.00408 [cs.CR]"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3024026"},{"key":"e_1_3_2_1_25_1","unstructured":"Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. arXiv:1411.1784 [cs.LG]  Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial Nets. arXiv:1411.1784 [cs.LG]"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.174"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00232"},{"key":"e_1_3_2_1_28_1","volume-title":"Fawkes: Protecting privacy against unauthorized deep learning models. In 29th {USENIX} Security Symposium ({USENIX} Security 20). 1589--1604.","author":"Shan Shawn","year":"2020","unstructured":"Shawn Shan , Emily Wenger , Jiayun Zhang , Huiying Li , Haitao Zheng , and Ben Y Zhao . 2020 . Fawkes: Protecting privacy against unauthorized deep learning models. In 29th {USENIX} Security Symposium ({USENIX} Security 20). 1589--1604. Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, and Ben Y Zhao. 2020. Fawkes: Protecting privacy against unauthorized deep learning models. In 29th {USENIX} Security Symposium ({USENIX} Security 20). 1589--1604."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.5555\/3298023.3298188"},{"key":"e_1_3_2_1_30_1","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton . 2008 . Visualizing data using t-SNE . Journal of machine learning research 9 , 11 (2008). Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of machine learning research 9, 11 (2008).","journal-title":"Journal of machine learning research"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00154"},{"key":"e_1_3_2_1_32_1","volume-title":"Li","author":"Yi Dong","year":"2014","unstructured":"Dong Yi , Zhen Lei , Shengcai Liao , and Stan Z . Li . 2014 . Learning Face Representation from Scratch . arXiv:1411.7923 [cs.CV] Dong Yi, Zhen Lei, Shengcai Liao, and Stan Z. Li. 2014. Learning Face Representation from Scratch. arXiv:1411.7923 [cs.CV]"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2603342"}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 30th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548110","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3503161.3548110","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:19Z","timestamp":1750186819000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548110"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":32,"alternative-id":["10.1145\/3503161.3548110","10.1145\/3503161"],"URL":"https:\/\/doi.org\/10.1145\/3503161.3548110","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}