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Existing deepfake-detection methods focus on passive detection, i.e., they detect fake face images via exploiting the artifacts produced during deepfake manipulation.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
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Anatol Z Tirkel, GA Rankin, RM Van Schyndel, WJ Ho, NRA Mee, and Charles F Osborne · 1993
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Ron G Van Schyndel, Andrew Z Tirkel, and Charles F Osborne · 1994
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Wai C Chu · 2003
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Robust dwt-svd domain image watermarking: embedding data in all frequencies
Emir Ganic and Ahmet M Eskicioglu · 2004
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Ali Al-Haj · 2007
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Dlib-ml: A machine learning toolkit
Davis E. King · 2009
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A dwt, dct and svd based watermarking technique to protect the image piracy
Md. Maklachur Rahman · 2013
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A deep learning approach to universal image manipulation detection using a new convolutional layer
Belhassen Bayar and Matthew C Stamm · 2016
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Face2face: Real-time face capture and reenactment of rgb videos
Justus Thies, Michael Zollhofer, Marc Stamminger, Christian Theobalt, and Matthias Nießner · 2016
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Recasting residual-based local descriptors as convolutional neural networks: an application to image forgery detection
Davide Cozzolino, Giovanni Poggi, and Luisa Verdoliva · 2017
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Distinguishing computer graphics from natural images using convolution neural networks
Nicolas Rahmouni, Vincent Nozick, Junichi Yamagishi, and Isao Echizen · 2017
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Two-stream neural networks for tampered face detection
Peng Zhou, Xintong Han, Vlad I Morariu, and Larry S Davis · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Mesonet: a compact facial video forgery detection network
Darius Afchar, Vincent Nozick, Junichi Yamagishi, and Isao Echizen · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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In ictu oculi: Exposing ai generated fake face videos by detecting eye blinking
Yuezun Li, Ming-Ching Chang, and Siwei Lyu · 2018
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Hidden: Hiding data with deep networks
Jiren Zhu, Russell Kaplan, Justin Johnson, and Li Fei-Fei · 2018
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Redmark: Framework for residual diffusion watermarking based on deep networks
Mahdi Ahmadi, Alireza Norouzi, Nader Karimi, Shadrokh Samavi, and Ali Emami · 2020
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The deepfake detection challenge dataset
Brian Dolhansky, Joanna Bitton, Ben Pflaum, Jikuo Lu, Russ Howes, Menglin Wang, and Cristian Canton Ferrer · 2020
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Leveraging frequency analysis for deep fake image recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Distortion agnostic deep watermarking
Xiyang Luo, Ruohan Zhan, Huiwen Chang, Feng Yang, and Peyman Milanfar · 2020
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Shruti Agarwal, Hany Farid, Yuming Gu, Mingming He, Koki Nagano, and Hao Li · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Exposing deepfake videos by detecting face warping artifacts
Yuezun Li and Siwei Lyu · 2019
Cited alongside, same era.
A novel two-stage separable deep learning framework for practical blind watermarking
Yang Liu, Mengxi Guo, Jian Zhang, Yuesheng Zhu, and Xiaodong Xie · 2019
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Exploiting visual artifacts to expose deepfakes and face manipulations
Falko Matern, Christian Riess, and Marc Stamminger · 2019
Cited alongside, same era.
Multi-task learning for detecting and segmenting manipulated facial images and videos
Huy H Nguyen, Fuming Fang, Junichi Yamagishi, and Isao Echizen · 2019
Cited alongside, same era.
Use of a capsule network to detect fake images and videos
Huy H Nguyen, Junichi Yamagishi, and Isao Echizen · 2019
Cited alongside, same era.
Learning efficient representations for fake speech detection
Nishant Subramani and Delip Rao · 2020
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Fakespotter: A simple yet robust baseline for spotting ai-synthesized fake faces
Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, and Yang Liu · 2020
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Cnn-generated images are surprisingly easy to spot…for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A Efros · 2020
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Udh: Universal deep hiding for steganography, watermarking, and light field messaging
Chaoning Zhang, Philipp Benz, Adil Karjauv, Geng Sun, and In So Kweon · 2020
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Understanding the security of deepfake detection
Xiaoyu Cao and Neil Zhenqiang Gong · 2021
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Beyond the spectrum: Detecting deepfakes via re-synthesis
Yang He, Ning Yu, Margret Keuper, and Mario Fritz · 2021
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Dynamic inconsistency-aware deepfake video detection
Ziheng Hu, Hongtao Xie, YuXin Wang, Jiahong Li, Zhongyuan Wang, and Yongdong Zhang · 2021
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Faceswap1
Online · 2021
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Faceswap2
Online · 2021
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Trump-cage dataset
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Trump-cage example
Online · 2021
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Faketagger: Robust safeguards against deepfake dissemination via provenance tracking
Run Wang, Felix Juefei-Xu, Meng Luo, Yang Liu, and Lina Wang · 2021
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Detecting deepfake videos with temporal dropout 3dcnn
Daichi Zhang, Chenyu Li, Fanzhao Lin, Dan Zeng, and Shiming Ge · 2021
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