{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T02:02:12Z","timestamp":1791511332535,"version":"4.3.4"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T00:00:00Z","timestamp":1562025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the Defense Advanced Research Projects Agency (DARPA)"},{"name":"United States Air Force Research Laboratory (AFRL)"},{"name":"Google Faculty Research Award"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,2]]},"DOI":"10.1145\/3335203.3335724","type":"proceedings-article","created":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T08:53:20Z","timestamp":1562662400000},"page":"113-118","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":104,"title":["Exposing GAN-synthesized Faces Using Landmark Locations"],"prefix":"10.1145","author":[{"given":"Xin","family":"Yang","sequence":"first","affiliation":[{"name":"University at Albany, State University of New York, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuezun","family":"Li","sequence":"additional","affiliation":[{"name":"University at Albany, State University of New York, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honggang","family":"Qi","sequence":"additional","affiliation":[{"name":"University of the Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siwei","family":"Lyu","sequence":"additional","affiliation":[{"name":"University at Albany, State University of New York, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,7,2]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Miles Brundage, and Anil Anthony Bharath.","author":"Arulkumaran Kai","year":"2017","unstructured":"Kai Arulkumaran , Marc Peter Deisenroth , Miles Brundage, and Anil Anthony Bharath. 2017 . A brief survey of deep reinforcement learning. arXiv preprint arXiv:1708.05866 (2017). Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, and Anil Anthony Bharath. 2017. A brief survey of deep reinforcement learning. arXiv preprint arXiv:1708.05866 (2017)."},{"key":"e_1_3_2_1_2_1","volume-title":"Began: Boundary equilibrium generative adversarial networks. arXiv preprint arXiv:1703.10717","author":"Berthelot David","year":"2017","unstructured":"David Berthelot , Thomas Schumm , and Luke Metz . 2017 . Began: Boundary equilibrium generative adversarial networks. arXiv preprint arXiv:1703.10717 (2017). David Berthelot, Thomas Schumm, and Luke Metz. 2017. Began: Boundary equilibrium generative adversarial networks. arXiv preprint arXiv:1703.10717 (2017)."},{"key":"e_1_3_2_1_3_1","volume-title":"A tutorial survey of architectures, algorithms, and applications for deep learning. APSIPA Transactions on Signal and Information Processing 3","author":"Deng Li","year":"2014","unstructured":"Li Deng . 2014. A tutorial survey of architectures, algorithms, and applications for deep learning. APSIPA Transactions on Signal and Information Processing 3 ( 2014 ). Li Deng. 2014. A tutorial survey of architectures, algorithms, and applications for deep learning. APSIPA Transactions on Signal and Information Processing 3 (2014)."},{"key":"e_1_3_2_1_4_1","volume-title":"Deep Learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016. Deep Learning . MIT Press . http:\/\/www.deeplearningbook.org. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_1_5_1","unstructured":"Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS.   Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS."},{"key":"e_1_3_2_1_6_1","unstructured":"Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In Advances in Neural Information Processing Systems. 5767--5777.   Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In Advances in Neural Information Processing Systems. 5767--5777."},{"key":"e_1_3_2_1_7_1","volume-title":"Progressive growing of gans for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196","author":"Karras Tero","year":"2017","unstructured":"Tero Karras , Timo Aila , Samuli Laine , and Jaakko Lehtinen . 2017. Progressive growing of gans for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196 ( 2017 ). Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen. 2017. Progressive growing of gans for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196 (2017)."},{"key":"e_1_3_2_1_8_1","volume-title":"A style-based generator architecture for generative adversarial networks. arXiv preprint arXiv:1812.04948","author":"Karras Tero","year":"2018","unstructured":"Tero Karras , Samuli Laine , and Timo Aila . 2018. A style-based generator architecture for generative adversarial networks. arXiv preprint arXiv:1812.04948 ( 2018 ). Tero Karras, Samuli Laine, and Timo Aila. 2018. A style-based generator architecture for generative adversarial networks. arXiv preprint arXiv:1812.04948 (2018)."},{"key":"e_1_3_2_1_9_1","volume-title":"How to train your DRAGAN. arXiv preprint arXiv:1705.07215 2, 4","author":"Kodali Naveen","year":"2017","unstructured":"Naveen Kodali , Jacob Abernethy , James Hays , and Zsolt Kira . 2017. How to train your DRAGAN. arXiv preprint arXiv:1705.07215 2, 4 ( 2017 ). Naveen Kodali, Jacob Abernethy, James Hays, and Zsolt Kira. 2017. How to train your DRAGAN. arXiv preprint arXiv:1705.07215 2, 4 (2017)."},{"key":"e_1_3_2_1_10_1","volume-title":"Detection of deep network generated images using disparities in color components. arXiv preprint arXiv:1808.07276","author":"Li Haodong","year":"2018","unstructured":"Haodong Li , Bin Li , Shunquan Tan , and Jiwu Huang . 2018. Detection of deep network generated images using disparities in color components. arXiv preprint arXiv:1808.07276 ( 2018 ). Haodong Li, Bin Li, Shunquan Tan, and Jiwu Huang. 2018. Detection of deep network generated images using disparities in color components. arXiv preprint arXiv:1808.07276 (2018)."},{"key":"e_1_3_2_1_11_1","unstructured":"Ming-Yu Liu and Oncel Tuzel. 2016. Coupled generative adversarial networks. In Advances in neural information processing systems. 469--477.   Ming-Yu Liu and Oncel Tuzel. 2016. Coupled generative adversarial networks. In Advances in neural information processing systems. 469--477."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"e_1_3_2_1_13_1","volume-title":"Detecting GAN-generated Imagery using Color Cues. arXiv preprint arXiv:1812.08247","author":"McCloskey Scott","year":"2018","unstructured":"Scott McCloskey and Michael Albright . 2018. Detecting GAN-generated Imagery using Color Cues. arXiv preprint arXiv:1812.08247 ( 2018 ). Scott McCloskey and Michael Albright. 2018. Detecting GAN-generated Imagery using Color Cues. arXiv preprint arXiv:1812.08247 (2018)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3206004.3206009"},{"key":"e_1_3_2_1_15_1","volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434","author":"Radford Alec","year":"2015","unstructured":"Alec Radford , Luke Metz , and Soumith Chintala . 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 ( 2015 ). Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)."},{"key":"e_1_3_2_1_16_1","volume-title":"Faceforensics: A large-scale video dataset for forgery detection in human faces. arXiv preprint arXiv:1803.09179","author":"R\u00f6ssler Andreas","year":"2018","unstructured":"Andreas R\u00f6ssler , Davide Cozzolino , Luisa Verdoliva , Christian Riess , Justus Thies , and Matthias Nie\u00dfner . 2018 . Faceforensics: A large-scale video dataset for forgery detection in human faces. arXiv preprint arXiv:1803.09179 (2018). Andreas R\u00f6ssler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nie\u00dfner. 2018. Faceforensics: A large-scale video dataset for forgery detection in human faces. arXiv preprint arXiv:1803.09179 (2018)."},{"key":"e_1_3_2_1_17_1","unstructured":"Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved techniques for training gans. In Advances in neural information processing systems. 2234--2242.   Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved techniques for training gans. In Advances in neural information processing systems. 2234--2242."},{"key":"e_1_3_2_1_18_1","unstructured":"Tim Salimans and Durk P Kingma. 2016. Weight normalization: A simple reparameterization to accelerate training of deep neural networks. In Advances in Neural Information Processing Systems. 901--909.   Tim Salimans and Durk P Kingma. 2016. Weight normalization: A simple reparameterization to accelerate training of deep neural networks. In Advances in Neural Information Processing Systems. 901--909."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3267357.3267367"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2929464.2929475"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.88573"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.10.006"}],"event":{"name":"IH&MMSec '19: ACM Information Hiding and Multimedia Security Workshop","location":"Paris France","acronym":"IH&MMSec '19","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the ACM Workshop on Information Hiding and Multimedia Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3335203.3335724","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3335203.3335724","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:45:01Z","timestamp":1750189501000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3335203.3335724"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,2]]},"references-count":22,"alternative-id":["10.1145\/3335203.3335724","10.1145\/3335203"],"URL":"https:\/\/doi.org\/10.1145\/3335203.3335724","relation":{},"subject":[],"published":{"date-parts":[[2019,7,2]]},"assertion":[{"value":"2019-07-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}