Deepfake Detection Using XceptionNet
DOI:
https://doi.org/10.32628/IJSRST251222688Abstract
The rapid rise of synthetic media, especially deepfakes, has sparked major concerns around misinformation, identity fraud, and diminishing public confidence in visual content. As these altered videos grow increasingly realistic, there is a pressing demand for reliable and scalable detection methods. This paper explores the use of the XceptionNet convolutional neural network architecture for deepfake detection. The analysis is based on the FaceForensics++ dataset, which comprises more than 1.8 million manipulated images created with four sophisticated face manipulation methods: NeuralTextures, FaceSwap, Face2Face, and DeepFakes. Cropped facial images are used for binary classification which is a process of differentiating between authentic and fraudulent content. Experimental results; with an accuracy of over 95% on unprocessed, and high-quality videos; over 80% accuracy even when heavily compressed; demonstrate that XceptionNet significantly outperforms both human observers and traditional detection methods, particularly under conditions of image compression. These findings highlight the robustness of deep learning-based models and the critical role of domain-specific preprocessing in improving detection accuracy.
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References
Deepfakes github. https://github.com/ deepfakes/faceswap. Accessed: 2018-10-29. 1, 2, 4, 14
Darius Afchar, Vincent Nozick, Junichi Yamagishi, and Isao Echizen. Mesonet: a compact facial video forgery detection network. arXiv preprint arXiv:1809.00888, 2018. 3, 6, 7, 13, 14
Fakeapp. https://www.fakeapp.com/. Accessed: 2018-09-01. 4
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan. YouTube-8m: A largescale video classification benchmark. arXiv preprint arXiv:1609.08675, 2016. 12
Faceswap. https://github.com/ MarekKowalski/FaceSwap/. Accessed: 2018-10-29. 1, 2
Haiying Guan, Mark Kozak, Eric Robertson, Yooyoung Lee, Amy N. Yates, Andrew Delgado, Daniel Zhou, Timothee Kheyrkhah, Jeff Smith, and Jonathan Fiscus. Mfc datasets: Large-scale benchmark datasets for media forensic challenge evaluation. In IEEE Winter Applications of Computer Vision Workshops, pages 63–72, Jan 2019. 3 2`21W
Grigory Antipov, Moez Baccouche, and Jean-Luc Dugelay. Face aging with conditional generative adversarial networks. In IEEE International Conference on Image Processing, 2017. 3
Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf, and Michael F. Cohen. Bringing portraits to life. ACM Transactions on Graphics (Proceeding of SIGGRAPH Asia 2017), 36(4):to appear, 2017. 3
Jawadul H. Bappy, Amit K. Roy-Chowdhury, Jason Bunk, Lakshmanan Nataraj, and B.S. Manjunath. Exploiting spatial structure for localizing manipulated image regions. In IEEE International Conference on Computer Vision, pages 4970– 4979, 2017. 3
Belhassen Bayar and Matthew C. Stamm. A deep learning approach to universal image manipulation detection using a new convolutional layer. In ACM Workshop on Information Hiding and Multimedia Security, pages 5–10, 2016. 3, 6, 7, 13, 14
Michael Zollhofer, Justus Thies, Darek Bradley, Pablo ¨ Garrido, Thabo Beeler, Patrick Peerez, Marc Stamminger, ´ Matthias Nießner, and Christian Theobalt. State of the art on monocular 3d face reconstruction, tracking, and applications. Computer Graphics Forum, 37(2):523–550, 2018. 1, 2
Luca Bondi, Silvia Lameri, David Guera, Paolo Bestagini, ¨ Edward J. Delp, and Stefano Tubaro. Tampering Detection and Localization through Clustering of Camera-Based CNN Features. In IEEE Computer Vision and Pattern Recognition Workshops, 2017. 3
Christoph Bregler, Michele Covell, and Malcolm Slaney. Video rewrite: Driving visual speech with audio. In 24th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’97, pages 353–360, 1997. 2
Francois Chollet. Xception: Deep Learning with Depthwise Separable Convolutions. In IEEE Conference on Computer Vision and Pattern Recognition, 2017. 6, 7, 13, 14
Valentina Conotter, Ecaterina Bodnari, Giulia Boato, and Hany Farid. Physiologically-based detection of computer generated faces in video. In IEEE International Conference on Image Processing, pages 1–5, Oct 2014. 3
Davide Cozzolino, Diego Gragnaniello, and Luisa Verdoliva. Image forgery detection through residual-based local descriptors and block-matching. In IEEE International Conference on Image Processing, pages 5297–5301, October 2014. 6
Davide Cozzolino, Giovanni Poggi, and Luisa Verdoliva. Recasting residual-based local descriptors as convolutional neural networks: an application to image forgery detection. In ACM Workshop on Information Hiding and Multimedia Security, pages 1–6, 2017. 3, 6, 7, 13, 14
Chris Frith. Role of facial expressions in social interactions. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1535), Dec. 2009. 1
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner. ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes. In IEEE Computer Vision and Pattern Recognition, 2017. 8
Kevin Dale, Kalyan Sunkavalli, Micah K. Johnson, Daniel Vlasic, Wojciech Matusik, and Hanspeter Pfister. Video face replacement. ACM Trans. Graph., 30(6):130:1–130:10, Dec. 2011. 2
Luca D’Amiano, Davide Cozzolino, Giovanni Poggi, and Luisa Verdoliva. A PatchMatch-based Dense-field Algorithm for Video Copy-Move Detection and Localization. IEEE Transactions on Circuits and Systems for Video Technology, in press, 2018. 3
Duc-Tien Dang-Nguyen, Giulia Boato, and Francesco De Natale. Identify computer generated characters by analysing facial expressions variation. In IEEE International Workshop on Information Forensics and Security, pages 252–257, 2012. 3
Tiago de Carvalho, Fabio A. Faria, Helio Pedrini, Ricardo da S. Torres, and Anderson Rocha. Illuminant-Based Transformed Spaces for Image Forensics. IEEE Transactions on Information Forensics and Security, 11(4):720–733, 2016. 3
Tiago de Carvalho, Christian Riess, Elli Angelopoulou, Helio Pedrini, and Anderson Rocha. Exposing digital image forgeries by illumination color classification. IEEE Transactions on Information Forensics and Security, 8(7):1182– 1194, 2013. 3
Xiangling Ding, Gaobo Yang, Ran Li, Lebing Zhang, Yue Li, and Xingming Sun. Identification of Motion-Compensated Frame Rate Up-Conversion Based on Residual Signal. IEEE Transactions on Circuits and Systems for Video Technology, in press, 2017. 3
Hany Farid. Photo Forensics. The MIT Press, 2016. 3
Jessica Fridrich and Jan Kodovsky. Rich Models for Ste- ´ ganalysis of Digital Images. IEEE Transactions on Information Forensics and Security, 7(3):868–882, June 2012. 6, 7, 13
Davide Cozzolino, Justus Thies, Andreas Rossler, Chris- ¨ tian Riess, Matthias Nießner, and Luisa Verdoliva. ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection. arXiv preprint arXiv:1812.02510, 2018. 8
Pablo Garrido, Levi Valgaerts, Ole Rehmsen, Thorsten Thormaehlen, Patrick Perez, and Christian Theobalt. Automatic ´ face reenactment. In IEEE Conference on Computer Vision and Pattern Recognition, pages 4217–4224, 2014. 2
Pablo Garrido, Levi Valgaerts, Hamid Sarmadi, Ingmar Steiner, Kiran Varanasi, Patrick Perez, and Christian ´ Theobalt. Vdub: Modifying face video of actors for plausible visual alignment to a dubbed audio track. Computer Graphics Forum, 34(2):193–204, 2015. 2
A. Gironi, Marco Fontani, Tiziano Bianchi, Alessandro Piva, and Mauro Barni. A video forensic technique for detection frame deletion and insertion. In IEEE International Conference on Acoustics, Speech and Signal Processing, pages 6226–6230, 2014. 3 [
Irene Amerini, Lamberto Ballan, Roberto Caldelli, Alberto Del Bimbo, and Giuseppe Serra. A SIFT-based forensic method for copy-move attack detection and transformation recovery. IEEE Transactions on Information Forensics and Security, 6(3):1099–1110, Mar. 2011. 3
David Guera and Edward J. Delp. Deepfake video detection ¨ using recurrent neural networks. In IEEE International Conference on Advanced Video and Signal Based Surveillance, 2018. 3
Rui Huang, Shu Zhang, Tianyu Li, and Ran He. Beyond face rotation: Global and local perception GAN for photorealistic and identity preserving frontal view synthesis. In IEEE International Conference on Computer Vision, 2017. 3
Minyoung Huh, Andrew Liu, Andrew Owens, and Alexei A. Efros. Fighting fake news: Image splice detection via learned self-consistency. In European Conference on Computer Vision, 2018. 3
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. Image-to-image translation with conditional adversarial networks. CVPR, 2017. 5, 14
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen. Progressive Growing of GANs for Improved Quality, Stability, and Variation. In International Conference on Learning Representations, 2018. 3
Ali Khodabakhsh, Raghavendra Ramachandra, Kiran Raja, Pankaj Wasnik, and Christoph Busch. Fake face detection methods: Can they be generalized? In International Conference of the Biometrics Special Interest Group, 2018. 3
Hyeongwoo Kim, Pablo Garrido, Ayush Tewari, Weipeng Xu, Justus Thies, Matthias Nießner, Patrick Perez, Chris- ´ tian Richardt, Michael Zollhofer, and Christian Theobalt. ¨ Deep Video Portraits. ACM Transactions on Graphics 2018 (TOG), 2018. 3, 5
Davis E. King. Dlib-ml: A machine learning toolkit. Journal of Machine Learning Research, 10:1755–1758, 2009. 12
Pavel Korshunov and Sebastien Marcel. Deepfakes: a new threat to face recognition? assessment and detection. arXiv preprint arXiv:1812.08685, 2018. 3
Pawel Korus and Jiwu Huang. Multi-scale Analysis Strategies in PRNU-based Tampering Localization. IEEE Transactions on Information Forensics and Security, 12(4):809–824, Apr. 2017. 3
Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, and Marc’Aurelio Ranzato Ludovic Denoyer. Fader networks: Manipulating images by sliding attributes. CoRR, abs/1706.00409, 2017. 3
Yuezun Li, Ming-Ching Chang, and Siwei Lyu. In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking. In IEEE WIFS, 2018. 3
Chengjiang Long, Eric Smith, Arslan Basharat, and Anthony Hoogs. A C3D-based Convolutional Neural Network for Frame Dropping Detection in a Single Video Shot. In IEEE Computer Vision and Pattern Recognition Workshops, pages 1898–1906, 2017. 3
Yongyi Lu, Yu-Wing Tai, and Chi-Keung Tang. Conditional cyclegan for attribute guided face image generation. In European Conference on Computer Vision, 2018. 3
Zhihe Lu, Zhihang Li, Jie Cao, Ran He, and Zhenan Sun. Recent progress of face image synthesis. In IAPR Asian Conference on Pattern Recognition, 2017. 3
Patrick Mullan, Davide Cozzolino, Luisa Verdoliva, and Christian Riess. Residual-based forensic comparison of video sequences. In IEEE International Conference on Image Processing, 2017. 3
Patrick Perez, Michel Gangnet, and Andrew Blake. Pois- ´ son image editing. ACM Transactions on graphics (TOG), 22(3):313–318, 2003. 4, 14
Ramachandra Raghavendra, Kiran B. Raja, Sushma Venkatesh, and Christoph Busch. Transferable Deep-CNN features for detecting digital and print-scanned morphed face images. In IEEE Computer Vision and Pattern Recognition Workshops, 2017. 3
Nicolas Rahmouni, Vincent Nozick, Junichi Yamagishi, and Isao Echizen. Distinguishing computer graphics from natural images using convolution neural networks. In IEEE Workshop on Information Forensics and Security, pages 1–6, 2017. 3, 6, 7, 13, 14
Andreas Rossler, Davide Cozzolino, Luisa Verdoliva, Chris- ¨ tian Riess, Justus Thies, and Matthias Nießner. FaceForensics: A large-scale video dataset for forgery detection in human faces. arXiv, 2018. 3
Husrev T. Sencar and Nasir Memon. Digital Image Forensics — There is More to a Picture than Meets the Eye. Springer, 2013. 3
Wenzhe Shi, Jose Caballero, Ferenc Huszar, Johannes Totz, ´ Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1874–1883, 2016. 14
Supasorn Suwajanakorn, Steven M. Seitz, and Ira Kemelmacher-Shlizerman. Synthesizing Obama: learning lip sync from audio. ACM Transactions on Graphics (TOG), 36(4), 2017. 1, 3
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi. Inception-v4, inception-resnet and the impact of residual connections on learning. 2017. 6
Justus Thies, Michael Zollhofer, and Matthias Nießner. De- ¨ ferred neural rendering: Image synthesis using neural textures. ACM Transactions on Graphics 2019 (TOG), 2019. 1, 2, 3, 4, 14
Justus Thies, Michael Zollhofer, Matthias Nießner, Levi Val- ¨ gaerts, Marc Stamminger, and Christian Theobalt. Real-time expression transfer for facial reenactment. ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2015, 34(6):Art. No. 183, 2015. 2
Justus Thies, Michael Zollhofer, Marc Stamminger, Chris- ¨ tian Theobalt, and Matthias Nießner. Face2Face: Real-Time Face Capture and Reenactment of RGB Videos. In IEEE Conference on Computer Vision and Pattern Recognition, pages 2387–2395, June 2016. 1, 2, 3, 4, 5, 12
Justus Thies, Michael Zollhofer, Marc Stamminger, Chris- ¨ tian Theobalt, and Matthias Nießner. FaceVR: Real-Time Gaze-Aware Facial Reenactment in Virtual Reality. ACM Transactions on Graphics (TOG), 2018. 3
Justus Thies, Michael Zollhofer, Christian Theobalt, Marc ¨ Stamminger, and Matthias Nießner. Headon: Real-time reenactment of human portrait videos. arXiv preprint arXiv:1805.11729, 2018. 3
Paul Upchurch, Jacob Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala, and Kilian Weinberger. Deep feature interpolation for image content changes. In IEEE Conference on Computer Vision and Pattern Recognition, 2017. 3
Weihong Wang and Hany Farid. Exposing Digital Forgeries in Interlaced and Deinterlaced Video. IEEE Transactions on Information Forensics and Security, 2(3):438–449, 2007. 3
Markos Zampoglou, Symeon Papadopoulos, , and Yiannis Kompatsiaris. Detecting image splicing in the wild (Web). In IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2015. 3
Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, and Yu Qiao. Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters, 23(10):1499–1503, Oct 2016. 14
Peng Zhou, Xintong Han, Vlad I. Morariu, and Larry S. Davis. Two-stream neural networks for tampered face detection. In IEEE Computer Vision and Pattern Recognition Workshops, pages 1831–1839, 2017. 3
Peng Zhou, Xintong Han, Vlad I. Morariu, and Larry S. Davis. Learning rich features for image manipulation detection. In CVPR, 2018. 3
Paolo Bestagini, Simone Milani, Marco Tagliasacchi, and Stefano Tubaro. Local tampering detection in video sequences. In IEEE International Workshop on Multimedia Signal Processing, pages 488–493, October 2013. 3
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