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Fairness of deepfake detectors in the presence of anomalies are not well investigated, especially if those anomalies are more prominent in either male or female subjects.
Going Deeper With Convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015 · 2015
Earlier work this paper cites.
Xception: Deep learning with depthwise separable convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 1251–1258
François Chollet. 2017 · 2017
Earlier work this paper cites.
MesoNet: a Compact Facial Video Forgery Detection Network
Darius Afchar, Vincent Nozick, Junichi Yamagishi, and Isao Echizen. 2018 · 2018
Earlier work this paper cites.
FaceForensics++: Learning to Detect Manipulated Facial Images. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)
Andreas Rossler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Niessner. 2019 · 2019
Earlier work this paper cites.
Efficientnet: Rethinking model scaling for convolutional neural networks. In International Conference on Machine Learning . PMLR, 6105–6114
Mingxing Tan and Quoc Le. 2019 · 2019
Earlier work this paper cites.
Swapped face detection using Deep Learning and Subjective Assessment - EURASIP Journal on Information Security
Xinyi Ding, Zohreh Raziei, Eric C. Larson, Eli V. Olinick, Paul Krueger, and Michael Hahsler. 2020 · 2020
Cited alongside, same era.
Face X-Ray for More General Face Forgery Detection. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, and Baining Guo. 2020 · 2020
Cited alongside, same era.
Metamorphic Filtering of Black-Box Adversarial Attacks on Multi-Network Face Recognition Models. In Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops . 410–417
Rohan Reddy Mekala, Adam Porter, and Mikael Lindvall. 2020 · 2020
Cited alongside, same era.
Bias in data-driven artificial intelligence systems—An introductory survey
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernandez, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, and Steffen Staab. 2020 · 2020
Cited alongside, same era.
A survey on bias and fairness in machine learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan. 2021 · 2021
Later among the works it cites.
Adversarial threats to deepfake detection: A practical perspective. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 923–932
Paarth Neekhara, Brian Dolhansky, Joanna Bitton, and Cristian Canton Ferrer. 2021 · 2021
Later among the works it cites.
DeepFake Creation and Detection:A Survey. In 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) . 584–588
Swathi P and Saritha Sk. 2021 · 2021
Later among the works it cites.
Robustness Evaluation of Stacked Generative Adversarial Networks using Metamorphic Testing
Hyejin Park, Taaha Waseem, Wen Qi Teo, Ying Hwei Low, Mei Kuan Lim, and Chun Yong Chong. 2021 · 2021
Later among the works it cites.
An Examination of Fairness of AI Models for Deepfake Detection. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 . International Joint Conferences on Artificial Intelligence Organization, 567–574
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Metamorphic object insertion for testing object detection systems. In 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 1053–1065
Shuai Wang and Zhendong Su. 2020 · 2020
Cited alongside, same era.
Loc Trinh and Yan Liu. 2021 · 2021
Later among the works it cites.